Electronic ink processing

ABSTRACT

Systems, methods, and computer-readable media for making rich, flexible, and more natural electronic ink annotations in an electronic document include creating a first context node associated with a first portion of a base portion of an electronic document; creating a second context node associated with an annotation to the base portion; and linking the second context node with the first context node.

FIELD OF THE INVENTION

The present invention relates to the processing of electronic ink.Various aspects of the present invention are particularly applicable tothe analysis of electronic ink, including layout analysis,classification, and recognition of electronic ink. Additional aspects ofthe invention relate to use of the layout-analyzed, classified, andrecognized electronic ink, for example, in providing rich and flexibleannotations in an electronic ink document.

BACKGROUND OF THE INVENTION

As the role of computers has expanded in society, various differenttechniques have been developed for entering data into computers. Oneparticularly useful technique for submitting data is throughhandwriting. By writing with a stylus or another object onto a digitizerto produce “electronic ink,” a computer user can forego the bulk andinconvenience associated with a keyboard. Handwriting input convenientlymay be used, for example, by doctors making rounds, architects on abuilding site, couriers delivering packages, warehouse workers walkingaround a warehouse, and in any situation when the use of a keyboardwould be awkward or inconvenient. While handwriting input is moreconvenient than keyboard input in many situations, text written inelectronic ink typically cannot be directly manipulated by most softwareapplications. Instead, text written in electronic ink must be analyzedto convert it into another form, such as ASCII characters. This analysisincludes a handwriting recognition process, which recognizes charactersbased upon various relationships between individual electronic inkstrokes making up a word of electronic ink.

Handwriting recognition algorithms have improved dramatically in recentyears, but their accuracy can be reduced when electronic ink is writtenat an angle. Likewise, when separate groups of ink strokes cannot beeasily distinguished, such as when two words are written closelytogether, many recognition algorithms cannot accurately recognizeelectronic ink. Some recognition algorithms also may incorrectlyrecognize electronic ink as text when, in fact, the electronic ink isintended to be a drawing. For example, a user may annotate typewrittentext by writing an electronic ink stroke that underlines, highlights,circles or crosses through some portion of the typewritten text. Ahandwriting recognition algorithm might then incorrectly recognize theseannotation strokes as a dash, the number zero or the letter “O.”

The accuracy of many recognition algorithms can be greatly improved by“parsing” (e.g., by analyzing the layout of and/or “classifying”) theelectronic ink before using the handwriting recognition algorithm. Aclassification process typically determines whether an electronic inkstroke is part of a drawing (that is, a drawing ink stroke) or part ofhandwritten text (that is, a text ink stroke). Classification algorithmsfor identifying other stroke types also are possible. The layoutanalysis process typically groups electronic ink strokes into meaningfulassociations, such as words, lines and paragraphs. Layout analysis andclassification processes can thus be used to identify which strokes in acollection of electronic ink belong to a single word, which words of theelectronic ink are associated with a single line of text written inelectronic ink, and which lines of text written in the electronic inkare associated with a paragraph.

While layout analyzing and classifying ink can dramatically improve therecognition of electronic ink, many software application developers areunaware of the importance of these activities before recognizing theelectronic ink. Until recently, layout and classification algorithmswere not readily available for use with existing software applications.For example, the Microsoft® Windows XP Tablet PC Edition Version 2002operating system was typically sold with the Microsoft® Windows Journalsoftware application for storing, displaying and manipulating electronicink. While the Microsoft® Windows Journal software application employsan internal parser, until recently this parser was not accessible toother software applications run by the operating system.

While the parsing process from the Windows Journal software applicationis now separately accessible by other software applications, the use ofthis parser is not well known, and this parser cannot easily be employedwith many software applications, into which a user may desire to enterhandwriting input. Moreover, even if a software application developerwere to create a parser specifically for use with a desired softwareapplication (which itself may be a difficult and time-consumingprocess), execution of a parsing process may be quite time-consuming.For example, parsing just a few strokes of electronic ink using arelatively fast microprocessor may take a parser several seconds or evenseveral minutes. If a software application must halt operation until theparsing process is complete, the software application will become tooslow for practical use by most users.

Accordingly, there is a need for electronic ink processing techniquesthat can be employed by a variety of software applications to, forexample, analyze the layout of, classify, and/or recognize electronicink. Further, there is a need for electronic ink processing techniquesthat can process electronic ink while still allowing the softwareapplication employing the techniques to accept new electronic ink inputwithout invalidating the results of the ink processing.

BRIEF SUMMARY OF THE INVENTION

Advantageously, various examples of the invention provide electronic inkprocessing techniques that can be used by a variety of softwareapplications to process electronic ink. Further, these electronic inkprocessing techniques allow the electronic ink to be processedasynchronously with regard to the operation of the software applicationimplementing the techniques, so that the electronic ink can be processedwithout stopping or significantly delaying the operation of the softwareapplication. The software application can even continue to accept newelectronic ink input while previous electronic ink input is beingprocessed.

With various examples of the invention, elements in a file or documentmay be described based upon their spatial position relative to eachother. For example, both an electronic ink stroke and typewritten textmay be described in terms of the same spatial coordinate system. Usingspatial information to describe the elements of a document, the softwareapplication managing the document can maintain a data structuredescribing the relationship between its document elements. Inparticular, the software application can maintain a data structure bothdescribing the class of the various document elements and definingassociations between the various document elements. These associationscan be defined, for example, as information used to link electronic inkstroke data or collections thereof to other elements in the electronicdocument (such as words, lines, paragraphs, drawings, table cells,etc.).

By describing document elements in a file or document data structurebased upon their spatial position, document elements for a variety offile types can employ common techniques for identifying and manipulatingtheir document elements. More particularly, a variety of softwareapplications can describe document elements within a document based upontheir spatial position and employ this spatial position referencing touse common electronic ink analysis methods. Still further, by specifyinga particular region of a document for analysis, each softwareapplication can limit the analysis process to only desired elementswithin a document.

To analyze new electronic ink input into a document according to variousexamples of the invention, the software application managing thedocument modifies a data structure associated with the document toinclude the new ink to be analyzed. The software application thenprovides this data structure (or relevant portions thereof) to an inkanalysis tool, which copies some or all of the data structure foranalysis (and operates on this copy of the data that is independent ofthe application program's document data structure). The ink analysistool passes the copy to an analysis process, such as a parsing process(e.g., a layout analysis process and/or a classification process). Thesoftware application may resume its normal operation, includingreceiving new electronic ink input and/or other data, while the inkanalysis process(es) is (are) being performed. In addition to receivingnew electronic ink, any “other data” may be received by the applicationprogram, for example, data modifying a size, location, or content ofexisting ink, text, images, graphics, tables, flowcharts, diagrams, andthe like; data adding additional text, images, graphics, tables,flowcharts, diagrams, and the like; data deleting existing text, images,graphics, tables, flowcharts, diagrams, and the like. After all desiredanalysis processes are completed, the analysis results are returned tothe ink analysis tool.

Thus, various examples of systems and methods according to the inventionallow ink analysis processes to be executed asynchronously from theoperation of the software application employing the ink analysisprocess. This asynchronous operation allows a user to continue to employa software application without being delayed by the analysis process.Further, it allows multiple analysis processes to executesimultaneously.

In response to receiving the analysis results, the ink analysis toolobtains the current version of the electronic document's data structure(which may contain new and/or modified data entered while the analysisprocesses were performed) from the software application, and reconcilesthe analysis results with the current version of the data structure. Byreconciling the analysis results with the current version of the datastructure, various examples of the invention can avoid more complicatedtechniques, such as “locking,” to asynchronously access the data beingused by the software application. Instead, the reconciliation can becalled upon by any software application, without the need for complexinternal locking provisions.

After reconciling the analysis results with the current version of thedata structure, the ink analysis tool may then provide a copy of thereconciled analysis results to another analysis process, such as ahandwriting, recognition process. Again, the software application mayresume its normal operation, including receiving new electronic inkinput and/or other data, while the second ink analysis process(es) is(are) being performed. After all of the desired second analysisprocesses are completed, the results of the second analysis process arereturned to the ink analysis tool. The ink analysis tool then obtainsthe current version of the data structure from the software application(which again may include new and/or modified data), and reconciles thesecond analysis results with the current version of the data structure.The ink analysis tool then updates the data structure using thereconciled results of the second analysis process. Of course, any numberof ink analysis procedures and/or stages can be used without departingfrom the invention.

Use of the various ink analysis processes described above and thespatial information relating or linking the electronic ink data to otherfeatures of the electronic document also may be used to provide rich,flexible, and natural ink annotations in an electronic document. Forexample, aspects of the invention may be used to provide electronic inkannotations that dynamically move and/or otherwise change based onchanges made to the underlying document elements being annotated. Userstypically annotate documents in many different ways, e.g., they maycircle, underline, highlight or strikeout words; write notes in themargin; draw arrows or other pointers to annotations located in themargin; etc. Moreover, users make annotations on a wide variety ofdifferent document types, including, for example, text, spreadsheets,drawings, slide shows, tables, charts, graphs, flowcharts, etc.

Smoothly integrating electronic ink annotations into an electronicdocument requires that the annotations behave appropriately when theunderlying electronic document changes for any reason. For example, if auser circles a word in an electronic document (as an annotation) andthen adds text somewhere in the document before that word, this maycause the circled word to move. In this instance, the circle annotationshould move and stay with the word. As another example, if the user addsor removes characters from the circled word or otherwise changes itssize in any may, the circle annotation should stretch or contract toaccommodate the word's new size. Preferably, when the underlyingelectronic document reflows and/or updates the positions of itsconstituent elements (paragraphs, pictures, columns, etc.) relative toeach other and/or the page for any reason, the electronic inkannotations will also reposition and stay properly located with respectto the underlying text or other information. Unless the annotationsbehave in this manner with respect to the underlying electronic documenttext, it becomes impractical to edit or share live electronic documentsafter annotation, and a paper printout will still be the easiest andmost useful way to annotate.

Determining how to change the annotation appropriately will depend onvarious factors relating to the annotation and the electronic document.For example, appropriately changing the annotation in a reflow situationmay depend, for example, on the ability of the computing system (e.g.,the parser): (a) to identify the electronic ink as an annotation; (b) toidentify the type of electronic ink annotation; and (c) to identify therelationship of the electronic ink to a particular element in theunderlying electronic document. While it may be possible to query theuser for some or all of this type of information, such systems wouldproduce a much more cumbersome user experience than annotating on paper.Accordingly, in accordance with various aspects of the invention, theabove information may be deduced from: (1) the electronic ink itself and(2) the content of the underlying document, including the spatialposition of various elements in the document relative to the electronicink.

Because the determination of the meaning of the ink annotations can becomplex and difficult, it is highly impractical to expect that eachapplication program whose document a user might wish to annotate willindividually implement annotation identifying logic. Rather, it would bepreferably to provide a reusable component for assisting in thisannotation function that each application program can easily integrate.For example, just as a pen-based computing system's operating systemprovides components for the collection and rendering of electronic ink,it would be preferable for the operating system to provide a componentthat determines the meaning of ink annotations (also called the“annotation parser”) that can fairly easily be fluent in working withthe ink involved.

Identifying the underlying electronic document's content, however, posessubstantial difficulties in providing “smart” annotation ability. Forexample, various different application programs have extremely disparateways of storing, managing, and reflowing documents. The presentinvention provides a reusable annotation parser capable of determiningthe relation of possible ink annotations to various different types ofelectronic documents. Specifically, in accordance with some aspects ofthis invention, a mechanism is provided with the annotation parser thatcalls back to the application program to provide relevant informationrelating to the ink being parsed (e.g., information relating to theelectronic document in the spatial area corresponding to the inkannotation, to provide “context” to the ink annotation). The mechanismis easy enough to be practical to integrate into any document-basedapplication, and it is efficient enough to work for very large documents(which can be processed in sections, such as pages or the like).

The ink processing techniques according to various examples of theinvention thus allow a variety of software applications to performmultiple processes on electronic ink through the ink analysis tool.Moreover, a software application using these techniques can continue itsnormal operation during the analysis process, including receiving newelectronic ink input without necessarily invalidating the results of theanalysis processes.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects, features, and advantages of the presentinvention will be readily apparent and filly understood from thefollowing detailed description, taken in connection with the appendeddrawings, in which:

FIG. 1 illustrates a schematic diagram of a general-purpose digitalcomputing environment in which certain aspects of the present inventionmay be implemented;

FIG. 2 illustrates a pen-based personal computing (PC) environment inwhich certain aspects of the present invention may be implemented;

FIGS. 3 and 4 illustrate various features of example implementations ofaspects of the invention relating to electronic document annotation;

FIG. 5 illustrates general features of ink parsing of an electronicdocument;

FIGS. 6A through 6I illustrate example data structures useful inpracticing at least some aspects of this invention;

FIGS. 7A through 12B illustrate example electronic documents andassociated example data structures useful in processing electronic inkannotations of electronic documents;

FIGS. 13A through 14B illustrate example electronic documents andassociated example data structures useful in processing electronic flowchart features in electronic documents;

FIGS. 15A through 15C illustrate example electronic documents andassociated example data structures useful in processing electronic tablefeatures in electronic documents;

FIGS. 16A-16D illustrate a method of processing electronic ink accordingto various examples of the invention;

FIGS. 17, 19-21, and 23-26 illustrate the transfer of data objectsduring example ink analysis processes according to various examples ofthe invention;

FIGS. 18 and 22 illustrate simple data trees that may be manipulatedaccording to various examples of the invention;

FIG. 27 illustrates a flowchart showing a method of reconciling analysisresults with a current state of a document; and

FIG. 28 illustrates an arrangement for asynchronously analyzingelectronic ink according to still other examples of the invention.

DETAILED DESCRIPTION OF THE DRAWINGS

Terms

The following terms are used in this specification and, unless otherwisespecified or clear from the context, the terms have the meaningsprovided below:

“Render” or “Rendered” or “Rendering”—The process of determining howinformation (including text, graphics, and/or electronic ink) is to bedisplayed, whether on a screen, printed, or output in some other manner.

“Computer-Readable Medium”—any available media that can be accessed by auser on a computer system. By way of example, and not limitation,“computer-readable media” may include computer storage media andcommunication media. “Computer storage media” includes volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information, such as computer-readableinstructions, data structures, program modules or other data. “Computerstorage media” includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology; CD-ROM, digital versatile disks (DVD)or other optical storage devices; magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices; or any othermedium that can be used to store the desired information and that can beaccessed by a computer. “Communication media” typically embodiescomputer-readable instructions, data structures, program modules orother data in a modulated data signal, such as a carrier wave or othertransport mechanism, and includes any information delivery media. Theterm “modulated data signal” means a signal that has one or more of itscharacteristics set or changed in such a manner as to encode informationin the signal. By way of example, and not limitation, communicationmedia includes wired media, such as a wired network or direct-wiredconnection, and wireless media, such as acoustic, RF, infrared and otherwireless media. Combinations of any of the above should also be includedwithin the scope of “computer-readable media.”

Overview

According to various examples of the invention, the properties of anelement in a document (or other type of file) may include informationrelating to the spatial position of that element within the document.Thus, both an electronic ink stroke and typewritten text may bedescribed in terms of the same spatial coordinate system for a documentand/or in terms of a spatial relationship or other relationship to otherelements in the document. Moreover, related elements in a document canbe identified simply by identifying the spatial region of the documentcontaining those elements and/or by linking those elements.

Using this spatial relationship between various documents elements, asoftware application may create and maintain a data structure thatdescribes other relationships between the document elements. Forexample, a software application may maintain a data structure, such as adata tree, that defines a class for various elements in a document.Thus, a node in the data structure might correspond to a handwrittenword or drawing containing one or more ink strokes, and data stored inthe node may further indicate a position of that word on a page. Anyother suitable or conventional data typically stored relating to an inkstroke and/or an electronic ink word also may be stored in the wordnode.

This type of data structure also may associate document elements (suchas individual ink strokes or typewritten text characters) intomeaningful groups, such as words, lines of words, sentences, paragraphs,and the like. Thus, if a software application maintains a document treestructure that describes a paragraph of handwritten electronic ink, theleaf nodes of the data structure may include data relating to theindividual strokes of electronic ink, and one or more strokes may beassociated together in the data structure as word nodes corresponding tothe words in the paragraph (e.g., words as determined by the parserand/or the recognizer). The tree structure may then associate the wordnodes with line nodes corresponding to lines in the paragraph. Each linenode further may be associated with a node corresponding to theparagraph. Further, a software application may maintain a tree or otherdata structure that associates a node corresponding to an electronic inkstroke and/or some other grouping of electronic ink with another nodecorresponding to a non-ink document element, such as an image; an inkdrawing; a typewritten character, word, line, paragraph; or the like.These data structures thus can be used to define relationships betweenassociated electronic ink strokes, to differentiate electronic inkstrokes forming handwritten text from electronic ink strokes annotatingnon-ink document elements, and/or to link electronic ink strokes toother document elements.

As will be discussed in detail below, these data structures can be usedwith an ink analysis tool according to various examples of the inventionto analyze electronic ink in a document. According to various examplesof the invention, a software application may obtain an analysis ofelectronic ink within a document by first creating a data structure forthe document. The data structure describes the relationship betweendocument elements that have already been analyzed (if any), and thusprovides the context in which any new electronic ink will be analyzed.This data structure or “analysis context object” also includes any newelectronic ink that has not been analyzed. That is, the analysis contextobject also includes electronic ink for which a relationship with otherdocuments elements has not yet been established. For some examples ofthe invention, the software application creates the analysis contextobject on its own. With other examples of the invention, however, thesoftware application employs the ink analysis tool or another tool tocreate the analysis context object.

After the software application has provided the analysis context objectto the ink analysis tool (or the ink analysis tool creates the analysiscontext object), the ink analysis tool makes a copy of or retrievesinformation relating to at least a portion of the analysis contextobject containing the unanalyzed electronic ink. By making a copy of orreceiving information relating to a desired portion of the analysiscontext object, the ink analysis tool creates a data structure that cansubsequently be analyzed without changing the analysis context objectmaintained by the software application. That is, the copy is independentof the actual electronic document used in the software application, andthus may be referred to below as the “document independent” analysiscontext object.

Once the ink analysis tool has created the document independent analysiscontext object, the ink analysis tool provides this document independentanalysis context object to one or more analysis processes. For example,if handwriting recognition is to be performed on the unanalyzedelectronic ink in the document, then the ink analysis tool may providethe document independent analysis context object to classifying and/orlayout analysis processes for classifying the ink into text and drawingstrokes (if necessary or desired) and then grouping the unanalyzedelectronic ink text strokes into associated groupings based on the inklayout. While the classifying and/or layout analysis processes areanalyzing the document independent analysis context object, the softwareapplication may continue with its regular operation. In particular, thesoftware application may continue to receive new electronic ink inputand/or any other data in the electronic document kept by the applicationprogram.

When the analysis process, such as a parsing process, has completed itsanalysis of the document independent analysis context object, it returnsthe analysis results to the ink analysis tool. More particularly, theparsing process (which may include, inter alia, classification andlayout analysis processes as described above) will return a modifiedversion of the document independent analysis context object showing newrelationships for the previously unanalyzed electronic ink. Because thesoftware application is free to accept new electronic ink input and/orany other data for the document during the above-described parsingoperation, however, the current version of the analysis context objectfor the document (i.e., the version maintained by the application) maybe different than both the document independent analysis context objectoriginally provided to the ink analysis tool and the parsing resultsprovided by the parsing process.

Accordingly, with some examples of the invention, the ink analysis toolmay obtain a current version of the analysis context object from thesoftware application, and reconcile the parsing results with the currentversion of the analysis context object. During this reconciliationprocess, the ink analysis tool will update the current version of theanalysis context object to reflect the results of the parsing process.The ink analysis tool will then pass the reconciled data from thecurrent analysis context object on to a handwriting recognition processfor recognition. With other examples of the invention, however, the inkanalysis tool may omit the reconciliation process, and instead pass theparsing results directly on to a handwriting recognition process.

Once the parsing results have been reconciled with the current versionof the analysis context object, the software application may againreturn to its regular operation, and thus it may continue to receive newelectronic ink input and/or any other data relating to the document. Inthe meantime, the recognition process analyzes the reconciled data fromthe current analysis context object (or, alternately, the parsingresults). After the recognition process has completed its analysis ofthe reconciled data (or parsing results), it returns its recognitionresults to the ink analysis tool. Again, because the softwareapplication may have received new electronic ink input and/or any otherdata for the document during the operation of the recognition process,the ink analysis tool obtains a current version of the analysis contextobject from the software application. The ink analysis tool thenreconciles the results from the recognition process with the currentversion of the analysis context object to update the current version ofthe analysis context object with the recognition results.

Example Operating Environment

FIG. 1 illustrates a schematic diagram of a general-purpose digitalcomputing environment that can be used to implement various aspects ofthe present invention. In FIG. 1, a computer 100 includes a processingunit 110, a system memory 120, and a system bus 130 that couples varioussystem components including the system memory 120 to the processing unit110. The system bus 130 may be any of several types of bus structuresincluding a memory bus or memory controller, a peripheral bus, and alocal bus using any of a variety of bus architectures. The system memory120 may include read only memory (ROM) 140 and random access memory(RAM) 150.

A basic input/output system 160 (BIOS), contains the basic routines thathelp to transfer information between elements within the computer 100,such as during start-up, is stored in the ROM 140. The computer 100 alsomay include a hard disk drive 170 for reading from and writing to a harddisk (not shown), a magnetic disk drive 180 for reading from or writingto a removable magnetic disk 190, and an optical disk drive 191 forreading from or writing to a removable optical disk 199, such as a CDROM or other optical media. The hard disk drive 170, magnetic disk drive180, and optical disk drive 191 are connected to the system bus 130 by ahard disk drive interface 192, a magnetic disk drive interface 193, andan optical disk drive interface 194, respectively. These drives andtheir associated computer-readable media provide nonvolatile storage ofcomputer-readable instructions, data structures, program modules, andother data for the personal computer 100. It will be appreciated bythose skilled in the art that other types of computer-readable mediathat can store data that is accessible by a computer, such as magneticcassettes, flash memory cards, digital video disks, Bernoullicartridges, random access memories (RAMs), read only memories (ROMs),and the like, may also be used in the example operating environment.

A number of program modules can be stored on the hard disk drive 170,magnetic disk 190, optical disk 199, ROM 140, or RAM 150, including anoperating system 195, one or more application programs 196, otherprogram modules 197, and program data 198. A user can enter commands andinformation into the computer 100 through input devices, such as akeyboard 101 and pointing device 102 (such as a mouse). Other inputdevices (not shown) may include a microphone, joystick, game pad,satellite dish, scanner, or the like. These and other input devices areoften connected to the processing unit 110 through a serial portinterface 106 that is coupled to the system bus 130, but they also maybe connected by other interfaces, such as a parallel port, game port, ora universal serial bus (USB), and the like. Further still, these devicesmay be coupled directly to the system bus 130 via an appropriateinterface (not shown).

A monitor 107 or other type of display device also may be connected tothe system bus 130 via an interface, such as a video adapter 108. Inaddition to the monitor 107, personal computers typically include otherperipheral output devices (not shown), such as speakers and printers. Inone example, a pen digitizer 165 and accompanying pen or stylus 166 areprovided in order to digitally capture freehand input. Although aconnection between the pen digitizer 165 and the serial port interface106 is shown in FIG. 1, in practice, the pen digitizer 165 may bedirectly coupled to the processing unit 110, or it may be coupled to theprocessing unit 110 in any suitable manner, such as via a parallel portor another interface and the system bus 130 as is known in the art.Furthermore, although the digitizer 165 is shown apart from the monitor107 in FIG. 1, the usable input area of the digitizer 165 may beco-extensive with the display area of the monitor 107. Further still,the digitizer 165 may be integrated in the monitor 107, or it may existas a separate device overlaying or otherwise appended to the monitor107.

The computer 100 can operate in a networked environment using logicalconnections to one or more remote computers, such as a remote computer109. The remote computer 109 can be a server, a router, a network PC, apeer device or other common network node, and it typically includes manyor all of the elements described above relative to the computer 100,although for simplicity, only a memory storage device 111 has beenillustrated in FIG. 1. The logical connections depicted in FIG. 1include a local area network (LAN) 112 and a wide area network (WAN)113. Such networking environments are commonplace in offices,enterprise-wide computer networks, intranets, and the Internet, usingboth wired and wireless connections.

When used in a LAN networking environment, the computer 100 is connectedto the local area network 112 through a network interface or adapter114. When used in a WAN networking environment, the personal computer100 typically includes a modem 115 or other means for establishing acommunications link over the wide area network 113, such as theInternet. The modem 115, which may be internal or external to thecomputer 100, may be connected to the system bus 130 via the serial portinterface 106. In a networked environment, program modules depictedrelative to the personal computer 100, or portions thereof, may bestored in the remote memory storage device.

It will be appreciated that the network connections shown are examplesand other techniques for establishing a communications link between thecomputers can be used. The existence of any of various well-knownprotocols such as TCP/IP, Ethernet, FTP, HTTP, UDP, and the like ispresumed, and the system can be operated in a user-server configurationto permit a user to retrieve web pages from a web-based server. Any ofvarious conventional web browsers can be used to display and manipulatedata on web pages.

Although the FIG. 1 environment shows an exemplary environment, it willbe understood that other computing environments also may be used. Forexample, one or more examples of the present invention may use anenvironment having fewer than all of the various aspects shown in FIG. 1and described above, and these aspects may appear in variouscombinations and subcombinations that will be apparent to one ofordinary skill.

FIG. 2 illustrates a pen-based personal computer (PC) 201 that can beused in accordance with various aspects of the present invention. Any orall of the features, subsystems, and functions in the system of FIG. 1can be included in the computer of FIG. 2. The pen-based personalcomputer system 201 includes a large display surface 202, e.g., adigitizing flat panel display, such as a liquid crystal display (LCD)screen, on which a plurality of windows 203 is displayed. Using stylus204, a user can select, highlight, and write on the digitizing displayarea. Examples of suitable digitizing display panels includeelectromagnetic pen digitizers, such as pen digitizers available fromMutoh Co. (now known as FinePoint Innovations Co.) or Wacom TechnologyCo. Other types of pen digitizers, e.g., optical digitizers, andtouch-sensitive digitizers may also be used. The pen-based computingsystem 201 interprets gestures made using stylus 204 in order tomanipulate data, enter text, and execute conventional computerapplication tasks, such as creating, editing, and modifyingspreadsheets, word processing programs, and the like.

The stylus 204 may be equipped with buttons or other features to augmentits capabilities. In one example, a stylus 204 could be implemented as a“pencil” or “pen”, in which one end constitutes a writing portion andthe other end constitutes an “eraser” end, and which, when moved acrossthe display, indicates portions of electronic ink on the display thatare to be erased. Other types of input devices, such as a mouse,trackball, keyboard, or the like also could be used. Additionally, auser's own finger could be used for selecting or indicating portions ofthe displayed image on a touch-sensitive or proximity-sensitive display.Consequently, the term “user input device,” as used herein, is intendedto have a broad definition and encompasses many variations on well-knowninput devices.

In various examples, the system provides an ink platform as a set of COM(component object model) services that an application program can use tocapture, manipulate, and store ink. The ink platform also may include amark-up language including a language like the extensible markuplanguage (XML). Further, the system may use DCOM as anotherimplementation. Yet further implementations may be used including theWin32 programming model and the Net programming model from MicrosoftCorporation. These platforms are commercially available and known in theart.

In addition to use with full performance pen-based computing systems or“tablet PCs” (e.g., convertible laptops or “slate” type tablet PCs),aspects of this invention can be used in conjunction with other types ofpen-based computing systems and/or other devices that accept data aselectronic ink and/or accept electronic pen or stylus input, such as:hand-held or palm-top computing systems; personal digital assistants;pocket personal computers; mobile and cellular telephones, pagers, andother communication devices; watches; appliances; and any other devicesor systems that include a monitor or other display device and/or adigitizer that presents printed or graphical information to users and/orallows input using an electronic pen or stylus, or which can processelectronic ink collected by another device (e.g., a conventional desktopcomputer that can process electronic ink collected by a tablet PC).

The invention now will be described in conjunction with the remainingfigures, which illustrate various examples of the invention andinformation to help explain the invention. The specific figures andinformation contained in this detailed description should not beconstrued as limiting the invention.

Spatial Document View Abstraction

As described above, certain aspects of the present invention relategenerally to systems and methods for providing richer and more versatileannotations using electronic ink in electronic documents. The followingdescribes various aspects and examples of this invention in more detail.

A. General Overview of the Invention

FIG. 3 generally illustrates operation of systems and methods accordingto at least some examples of this invention. Specifically, asillustrated in FIG. 3, a user may be interacting in some manner with anelectronic document 300 (Document “A” in FIG. 3), for example, by addingelectronic ink to the document 300. In the illustrated example, theelectronic document 300 includes electronic or typewritten text 302(“Sample Text” in the illustrated example) and an ink drawing 304 (ahouse in the illustrated example). Of course, the electronic document300 could include any data or information without departing from theinvention, such as electronic text, electronic ink (drawing or text),images, graphs, tables, charts, other graphic or electronic information,and/or combinations thereof. For the purposes of this example, assumethat the original electronic document 300 (also called the “basedocument” or “base portion” in this application) includes the electronictypewritten text 302 and the electronic ink drawing 304. As the userreviews Document A 300 in this example, she decides to include anelectronic ink annotation into the document 300. Specifically, in theillustrated example, the annotation includes a circle 306 around someportion 308 of the electronic text 302.

In this example, after the user enters the annotation, the applicationprogram will call the parser 310 and request parsing of the newly inputelectronic ink data (as noted above, “parsing” may include, for example,classification of the electronic ink into various ink types (e.g.,drawings, text, flowcharts, music, etc.) and/or ink layout analysis(e.g., ascertaining spatial and positional relationships among the inkstrokes and grouping them into appropriate groupings), as well as otheranalysis processes). Specifically, the application program will send theinput electronic ink data (representing the annotation 306, in thisexample) to the parser 310 as unclassified ink data. This is illustratedin FIG. 3 by input arrow 312.

Optionally, at or about this same time, the application program may sendsome or all of the data relating to the underlying electronic document300 to the parser 310. This data may include, for example, data relatingto the spatial layout of information in the document 300, such as thepositions of the electronic text 302, the drawing 304, etc.Additionally, the application program may send data indicating ahierarchical structure of the data in the document, which is describedin more detail below. As another alternative, as also described in moredetail below, the parser 310 may call back to the application programrequesting certain data relating to the electronic document 300, such asinformation relating to the electronic document 300 in the spatial areaassociated with the new, unclassified ink (in this instance, datarepresenting the typewritten text and information located spatially nearannotation 306). This data input to the parser 310 is illustrated inFIG. 3 by input arrow 314. Of course, both unclassified ink andpreviously analyzed data can be simultaneously sent to and/or madeavailable to the parser without departing from the invention.

The parser 310 takes the input electronic document data 314 and theinput unclassified ink data 312 and uses that information to classifythe new electronic ink data into an ink type. The ink may be classifiedinto various different ink types without departing from the invention,and various examples of possible ink types are described in more detailbelow. For the present example, based on the input ink 306 and theinformation 302 contained in the underlying document 300, the parser 310according to this example of the invention may determine and classifythe input ink 306 as an annotation or even more specifically, as an inkdrawing corresponding to a container annotation (e.g., a circle) thatcontains specific typewritten text. Of course, other annotations typesalso are possible, such as highlight annotations, “points to”annotations, “points from” annotations, anchor annotations (e.g.,without pointing to or pointing from), horizontal spans, vertical spans,and the like, and various examples are explained in more detail below.

Once parsed, data associated with the annotation 306 may be incorporatedinto a “document tree” hierarchical data structure associated with theelectronic document 300 (or any other suitable or desired datastructure), and that data structure (or instructions for modifying anexisting data structure maintained by the application program) may besent back to the application program, as indicated in FIG. 3 by arrow316. If desired, other data also can be returned from the parser 310 tothe application program without departing from the invention. Forexample, as indicated in FIG. 3, data associated with the results of arecognition analysis process (such as a handwriting recognizer or otherrecognizer) may be returned to the application program, if the parser310 action included calls to one or more recognizer modules, components,and/or programs.

FIG. 4 illustrates an example of an implementation 400 of variousfeatures used in some examples of this invention. As illustrated, anelectronic document (such as Document A 300 from FIG. 3) is generated,stored, and/or maintained by an application program 400 a as a datastructure or document model 402. This data structure 402 may be ahierarchical data structure or any other desired or suitable datastructure without departing from the invention. The application program400 a includes an “Analysis Context” object 404, which contains a mirrorcopy, a selective copy, or other relevant information relating to thedata structure 402 (e.g., the Analysis Context object 404 may be a“translation” layer in which queries on the Analysis Context object 404get translated into queries on the native document mode structure—inthis manner, the parsing technology in accordance with aspects of thisinvention may be translated for use with various different nativeapplication programs). The “platform” 400 b or operating system side ofthis example implementation 400 includes an “Ink Analyzer” method 406,which is called by the application program 400 a. The applicationprogram 400 a calls the Ink Analyzer method 406 and passes to itreference to the Analysis Context object 404. The Ink Analyzer method406 will call the parser 408 (also part of the platform 400 b in thisexample), which classifies and analyzes the layout of the input data, asgenerally described above. Operation of an example implementationaccording to the invention is described in more detail in the AnalysisOf Ink section below. Once the parser 408 completes its analysis andprocessing, the platform 400 b may send data back to the applicationprogram 400 a to enable the document model 402 and/or Analysis Contextobject 404 to rebuild its data structure based on the parser processingand results, as generally illustrated at arrow 410 in FIG. 4.

FIG. 5 generally illustrates an example of a data structure that may beused for storing electronic document data in at least some examples ofthis invention, for example, as part of the “Analysis Context” object404, as the document model 402, or as data structures generated and/oroutput by the parser 408. Specifically, in FIG. 5, an example electronicdocument 500 is illustrated. When stored as an Analysis Context object502 or subjected to parsing, the data structure may include the variousdocument elements classified or arranged into different groupings or“nodes.” For example, as illustrated in FIG. 5, the electronic document500 includes three electronic text paragraphs 504, 506, and 508; oneelectronic ink drawing 510; and one electronic ink annotation 512. Anexample Analysis Context data structure 502 for the electronic document500 is shown in FIG. 5 as a list of top-level elements. Specifically,node element 504(a) corresponds to paragraph 504 in electronic document500, node element 506(a) corresponds to paragraph 506 in electronicdocument 500, node element 508(a) corresponds to paragraph 508 inelectronic document 500, node element 510(a) corresponds to ink drawing510 in electronic document 500, and node element 512(a) corresponds tothe ink annotation 512 in electronic document 500. Additional nodes maybe stored in the data structure (e.g., in a hierarchical arrangement) asparent nodes and/or child nodes to the top level nodes 504 a, 506 a, 508a, 510 a, and 512 a illustrated in FIG. 5, as will be described in moredetail below.

B. Context Nodes and Hierarchical Data Structures

FIGS. 6A through 6I illustrate various examples of context nodes anddata structures that may be used in building, analyzing, and parsingelectronic document data, such as an Analysis Context object, inaccordance with some examples of this invention. FIG. 6A illustrates anexample data structure 600 that may be used for storing unclassifiedelectronic ink data (e.g., ink newly input by a user that has not beenpreviously subjected to parsing). This example data structure 600includes a root node 602 (which may correspond to the entire electronicdocument in the application program, a specific page of the document, orany suitable or desired grouping of data, such as a grouping used by theapplication program). Any suitable or desired data may be included inthe root node 602, such as page number, pointers to the previous pageand the next page, margin locations or dimensions, etc. Each root node602 may include any number of unclassified ink nodes 604 as child nodes,and each unclassified ink node 604 further may include any number ofindividual stroke nodes 606 (the last node in a hierarchical structure(the stroke node 606 in this example) also may be called a “leaf node”in this specification). (The letter “n” in the various figures canrepresent any number, including zero.) The various nodes of the datastructure 600 may include any desired or suitable data corresponding tothe node. For example, stroke nodes 606 may include data representing:digitizer points or other data identifying the electronic ink stroke;stroke position or orientation data; stroke color data; stroke pressuredata; stroke input timing data; stroke ID data; and/or any otherconventional or useful data used in storing stroke information insystems and methods capable of receiving electronic ink. Likewise, theunclassified ink node(s) 604 may include any desired or suitable dataassociated with the ink or the node, such as data representing: thebounding box size of all strokes contained within the node; the boundingbox location; input timing information; geometric information for theink (such as, for example, convex hull information); and/or any otherconventional or useful data relating to the unclassified ink strokesincluded in the node. Alternatively, if desired, stroke data generallymay be saved as a property of another node (e.g., of a word node, tablenode, or the like) rather than as a separate node in a document tree.

Once unclassified ink is sent to a classifier, layout analyzer, arecognizer, and/or another parsing system, at least some portions of theink may be associated together and/or classified into various differenttypes, and a data structure associated with the ink may be changed tocorrespond to the various associations and types into which it wasclassified. FIG. 6B illustrates an example data structure 610 forelectronic ink that has been classified as ink text. Using parsingtechnology, including conventional parsers known and used in the art,input electronic ink strokes (e.g., electronic ink data collectedbetween a pen-down event and a temporally following pen-up event or insome other manner) may be parsed and stored in a hierarchical mannerwherein related individual ink strokes may be grouped together andstored as ink words, linearly arranged ink words may be grouped togetherand stored as ink lines, related ink lines may be grouped together andstored as ink paragraphs, and related paragraphs may be stored aselectronic documents (e.g., in individual page portions, as entiredocuments, or in any suitable root grouping). An example hierarchicaldata structure 610 corresponding to electronic ink data parsed andstored in this manner, as illustrated in FIG. 6B, may include a rootnode 612, which may correspond to an entire electronic document, a page,or another grouping as used by the application program. Each root node612 may contain any number of nodes 614 corresponding to paragraphs orsimilar groupings of electronic ink strokes. Paragraph nodes 614 maycontain any number of individual line nodes 616, which in turn mayinclude any number of individual ink word nodes 618, which further maycontain any number of individual stroke nodes 620 corresponding to theindividual strokes of the input electronic ink data. Optionally, asnoted above, the stroke data may be stored as a “property” of anassociated word node, if desired. The various nodes 612, 614, 616, 618,and 620 may store any suitable data relating to the various individualstrokes or collections of strokes contained within the node, likespatial orientation or positioning data and/or other data like thatdescribed above.

Other data types and data structure arrangements corresponding to inputelectronic ink strokes are possible without departing from theinvention. For example, classifying, layout analysis, or recognizertechnology may determine that input electronic ink forms an ink drawing.FIG. 3 illustrates an example ink drawing 304 that contains severalindividual ink strokes. FIGS. 6C and 6D illustrate example hierarchicaldata structures that may be used for grouping and storing electronic inkdata determined to relate to ink drawings. As shown in FIG. 6C, datastructure 630 includes a root node 632 (which may correspond to theentire electronic document, an electronic page, or some other groupingof data, as described above). Each root node 632 may include any numberof individual ink drawing nodes 636 (e.g., such that each individualdrawing has an individual node storing data relating to, for example,drawing width, drawing height, drawing position, bounding box size, andthe like), and each ink drawing node 636 may include any number ofindividual ink stroke nodes 638 (corresponding to the individual inkstrokes making up the drawing). Optionally, the ink stroke data may bestored as a “property” of its corresponding ink drawing node (or othernode).

FIG. 6D illustrates an alternative data structure 630 a for electronicdocuments containing one or more ink drawings. In this example, anelectronic document or page or the other grouping of data (asrepresented by root node 632 a) may include one or more groups(represented by node 634 a) of electronic ink drawings with their dataassociated together and stored in the hierarchical manner described inconjunction with FIG. 6C (e.g., an entire electronic document(represented by root node 632 a) may include several individual pages(each represented by a group node 634 a), and each individual page mayhave one or more individual ink drawings (each represented by an inkdrawing node 636 a), and each individual ink drawing may contain one ormore individual ink strokes (each represented by a stroke node 638 a orin a property of the ink drawing node)). It should be noted that bothgroups and ink drawings may be children of the same root node or anygroup node. In addition, if desired, a group node may contain additionalgroup nodes. Of course, still other suitable data structures for storingelectronic ink drawings may be used without departing from thisinvention.

Hierarchical data structures, however, are not limited to use with inputelectronic ink data. Input typewritten text (e.g., from a keyboard) alsocan be associated into various groups and stored in a hierarchical datastructure. FIG. 6E illustrates an example of such a data structure 640.This data structure 640 may include a root node 642 (e.g., like the rootnodes discussed above). Each root note 642 may include any number oftext paragraph nodes 644 (corresponding to paragraphs of text), eachparagraph node 644 may include any number of text line nodes 646 (oralternatively, text sentence nodes), and each line node 646 may furtherinclude any number of individual text word nodes 648. If desired, textwords could be further broken into individual text character nodes, andstill further broken into individual character feature nodes (relatingto, for example, baseline, serif, ascender, and descender features ofeach character) without departing from the invention. The various nodescan store any suitable data relating to the text, such as paragraph,line, or word spatial position, content, size, and the like; pagemargins; margin dimensions or locations; number of pages; etc.

The various data structures described above in conjunction with FIGS. 6Athrough 6E illustrate data structures that exclusively contain onlyelectronic ink data or only electronic typewritten text data. Parsingtechnology may be used to analyze, combine, associate, and group thesedifferent data types in a single data structure without departing fromthe invention. FIG. 6F illustrates an example data structure 650 inwhich an electronic document or a portion thereof (represented by rootnode 652) contains one or more individual paragraphs (represented byparagraph node 654) and one or more individual lines (represented byline node 656). The lines potentially may contain both typewritten text(represented by text word node 658) and electronic ink text (representedby ink word node 660 and ink stroke node 662). Each individualparagraph, line, and word node (both typewritten text and ink words)will contain appropriate independent data, depending on the content ofthe paragraph, line, and word. Additionally or alternatively, individualwords could further include both ink characters and typewrittencharacters without departing from the invention.

Other electronic data also may be included in an electronic document'sdata structure (including hierarchical data structures) withoutdeparting from the invention. For example, image data (such as a digitalphoto, graphical information, and the like) may be included in a datastructure for an electronic document, for example, as shown in the datastructure 664 of FIG. 6G. As illustrated in this example, the datastructure 664 includes an electronic document or a portion thereof(represented by root node 666) that contains one or more individualgroupings of data (represented by group node 668). Each grouping of datain this example further may include an electronic image (represented byimage node 670), as well as typewritten text (represented by paragraphnode 672, line node 674, and text word node 676), as generally describedabove in conjunction with FIGS. 6E and 6F. Of course, a data structurelike that illustrated in FIG. 6G also could contain electronic ink data(e.g., like the data structures illustrated in FIGS. 6A through 6D) orother desired data types without departing from the invention.

FIG. 6H illustrates an example of another potential data structure 680that may be used in accordance with at least some examples of thisinvention. More specifically, the data structure 680 of FIG. 6Hcorresponds to an electronic document or portion thereof (represented byroot node 682) containing one or more lists (represented by list node684). A list in an electronic document may contain any number ofindividual list items (represented by list item node 686), and each listitem may contain a wide variety of different types of electronicinformation. For example, some list items optionally may include a listbullet, which may be comprised of a typewritten bullet or an electronicink bullet (an ink bullet node 688 including one or more correspondingink stroke nodes 690 are illustrated in the example of FIG. 6H). Inaddition, each list item optionally may include one or more electronicink paragraphs (represented by node chain 692), one or more ink drawings(represented by node chain 694), and/or one or more typewrittenparagraphs (represented by node chain 696). Additionally (oralternatively), each list item optionally may include one or more images(represented by image node 698) and/or one or more groupings of data,such as the groupings described above in conjunction with FIGS. 6D and6G (represented by group node chain 700). Because the various nodesand/or node chains 692, 694, 696, 698, 700 may generally correspond tothe example data structures illustrated in FIGS. 6A through 6G, as wellas to subsets and/or groupings of these data structures, furtherexplanation is omitted. If desired, in at least some instances, anindividual list item node 686 also may itself contain a list having adata structure like that illustrated in FIG. 6H.

FIG. 6I illustrates another example data structure 710 that may be usedin at least some examples of the present invention. This example datastructure 710 corresponds to electronic data analyzed, associatedtogether, grouped, and stored as a table. In this illustrated example,each electronic document or portion thereof (represented by root node712) may include one or more tables (represented by table node 714). Atable, in this example, may be comprised of one or more rows ofinformation (represented by row node 716), and every row may becomprised of one or more individual cells (represented by cell node718). The individual cells may contain one or more data structures,including, for example, any of the various different data structuresdescribed above. In the illustrated example, the individual table cellsare shown as potentially containing any number of images (represented byimage node 720), any number of typewritten text paragraphs (representedby node chain 722), any number of groupings (represented by node chain724), any number of ink drawings (represented by node chain 726), anynumber of additional tables (represented by node chain 728), and anynumber of lists (represented by node chain 730). Of course, any othersuitable or desired data structures may be included in a table withoutdeparting from this invention, including the various specific datastructures described above and/or combinations and subsets of datastructures, e.g., like those described above.

Any suitable or desired data can be stored in the various differentnodes, including the various types of data described above. For use withprocessing data relating to annotations, it may be useful in at leastsome examples of the invention for the various nodes to store datarelating to the spatial position, orientation, or location of the nodein the electronic document, optionally as this spatial informationrelates to or links with other nodes in the electronic document datastructure.

Also, other types of parsers, classifiers, and/or recognizers and datatypes may be used without departing from the invention. For example,recognizers may be used to analyze, recognize, group, and/or associateelectrical or electronic symbols (e.g., resistors, voltage sources,capacitors, etc.); musical symbols; mathematical symbols; flowchartelements; pie chart elements; and the like, without departing from theinvention.

The data structures illustrated in FIGS. 6A through 6I are merelyexamples of various data structures that may be used in accordance withaspects of this invention. Those skilled in the art will recognize thatthe specific data structures used may vary widely without departing fromthe invention. For example, different nodes representing differentlayout groupings may be used, additional node types may be added, orsome of the described node types may be omitted without departing fromthe invention (e.g., column nodes may be used instead of row nodes inthe table data structure). Additionally, the above description isoptimized for use with languages and text representations in whichcharacters are read from left-to-right and then top-to-bottom on a page.Data structures designed for use with and corresponding to otherlanguages and character arrangements, for example, data structures toaccommodate languages read and/or written from right-to-left,top-to-bottom, bottom-to-top, and combinations thereof, may be usedwithout departing from the invention. Additionally, if desired(particularly for some languages, such as Asian languages), strokes maybe appropriately grouped as characters, which may then be grouped intolines without using an intermediate “word” node, as described above. Asanother alternative, the use of line nodes may be omitted and word nodesmay be grouped together as paragraphs and/or in other desired groupings.These and other variations in the data structure, for example, toaccommodate characteristics of a particular language, may be usedwithout departing from the invention.

C. Application of Aspects of the Invention to Annotations

Aspects of the present invention, including the use of context nodes andhierarchical data structures as described above, may be used to provide“smart” electronic ink annotations in electronic documents. As describedabove, one desirable and advantageous use of pen-based computing systemsis in the annotation of electronic documents. However, to beparticularly useful and effective, annotations made in electronic ink indocuments on a pen-based computing system should be flexible enough sothat if and when characteristics associated with various elements in theunderlying document change for any reason (e.g., margin changes, displaysize changes, font changes, addition of information, deletion ofinformation, etc.), the annotation is capable of accurately changingposition and/or other characteristics based on changes to the annotatedelements in the underlying document. This may be accomplished, forexample, by linking at least one context node associated with theannotation to one or more context nodes associated with the underlyingdocument. In at least some instances, data and/or characteristicsassociated with and stored relating to the underlying document, such asdata relating to the spatial attributes, position, and/or location ofone or more document elements, can be used to control the location,appearance, and/or other characteristics of the annotation.

FIGS. 7A and 7B illustrate one example of an annotation that may beapplied to an electronic document via electronic ink. As illustrated inFIG. 7A, an electronic document 750 includes the sentence “Today the skyis green.” A user of a pen-based computing system has annotated thisdocument 750 using electronic ink to underline the word “green” (theunderline annotation is shown at reference number 752). FIG. 7Billustrates an example hierarchical data structure 760 corresponding tothis composite electronic document 750 (the entire electronic document750 is represented in the data structure 760 by root node 762). Oncefully parsed, the data structure 760 will include context nodes showingthe overall document structure. More specifically, information relatingto the typewritten text in the electronic document 750 will be analyzedand associated together to indicate that the electronic document 750contains one paragraph (paragraph node 764), the paragraph contains aline (line node 766), and the line contains five words (one text wordnode 768 a-768 e for each of the words “Today,” “the,” “sky,” “is,” and“green,” respectively). Additionally, the parser will note the presenceof data in the electronic document 750 relating to the annotation 752,and it will classify this data as an electronic ink drawing (ink drawingnode 770). Additionally, based on the location and position of the inkdrawing stroke(s) with respect to the typewritten text in the underlyingdocument 750, the parser will recognize and classify the annotation asan “underline” annotation and generate an underline node 772.Additionally, the parser will store all stroke data corresponding to theactual ink stroke(s) of the underline annotation in one or more strokeleaf nodes 774 (optionally, the stroke data may be stored as a propertyof the underline node 772 or another appropriate node).

Additionally, in order to maintain the electronic ink underline stroke752 with this individual word “green” wherever it appears in theelectronic document 750 (e.g., should the word move for any reason),data is saved in the data structure 760 of this example to indicate thatthe underline context node 772 (e.g., a “source” context node in thislinking example) is linked to the text word node 768 e for the word“green” (a “destination context” node in this example) as illustrated inFIG. 7B by arrow 776, and data is saved to indicate that the text wordnode 768 e is linked by the underline node 772, as indicated by arrow778. This linking “anchors” the underline node 772 to the text word node768 e (e.g., an “anchor” type link). Accordingly, if for any reason datastored in the text word context node 768 e indicates that a position ofthe word “green” has changed in the electronic document, the links 776and 778 will allow the application program to detect that, if possible,it should move the rendering of the underline annotation to the locationand/or spatial position of text word context node 768 e in the changedelectronic document. As another example, should the “bounding box” data,word width data, or other data stored in context node 768 e indicate aword size or position change for any reason (e.g., due to font sizechange, addition of characters, deletion of characters, change incharacters, etc.), the application program then may alter the size ofthe rendered underline (e.g., stretched or truncated), if possible, tocorrespond to the new size associated with the text word represented bycontext node 768 e. If applicable, systems and methods according to atleast some examples of the invention may break up the annotation'sstroke(s) to appear on more than one line, should changes to theunderlying document cause the annotated document element to appear onmultiple lines (e.g., because of words added, hyphenation, or the like).Also, any suitable linking arrangement between nodes or any suitabledata representing a link may be used without departing from theinvention.

FIGS. 8A and 8B illustrate another annotation example. In this example,as illustrated in FIG. 8A, the electronic document 800 again includesthe sentence “Today the sky is green,” but in this instance, a user of apen-based computing system has annotated the document 800 usingelectronic ink to strike out the word “green” (the strike-out is shownat reference number 802). FIG. 8B illustrates an example hierarchicaldata structure 810 corresponding to this composite electronic document800 once it is fully parsed (because the specific context nodes for muchof FIG. 8B correspond to the context nodes present in FIG. 7B, the samereference numbers as those present in FIG. 7B are used in FIG. 8B, andthe duplicative explanation is omitted). In this instance, the parserwill note the presence of data in the electronic document 800 relatingto the annotation 802, and it will classify this data as an electronicink drawing (ink drawing node 812). Additionally, based on the locationand position of the ink drawing stroke(s) with respect to the content ofthe underlying typewritten text in the document 800 (e.g., thestrike-out horizontally spans the text word), the parser will recognizeand classify the annotation as a “strike-out” annotation and generate astrike-out node 814. Additionally, the parser will store all stroke datacorresponding to the actual ink stroke(s) of the strikeout annotation inone or more stroke leaf nodes 816 (or alternatively, as a property inthe strike-out node 814 or another appropriate node).

As was the case with respect to the underline annotation described withrespect to FIGS. 7A and 7B, the strike-out annotation may be maintainedwith this individual word “green,” should the word move for any reason.Again, this may be accomplished, for example, by saving data in the datastructure 810 to indicate that the strike-out context node 814 (the“source” context node in this example) is linked to the text word node768 e for the word “green” (the “destination” context node in thisexample), as illustrated in FIG. 8B by arrow 818, and by saving data inthe data structure to indicate that the text word node 768 e is linkedby the strike-out node 814, as indicated by arrow 820. The link type inthis example is a “horizontally spanning” link type that anchors thestrikeout node 814 to the text word node 768 e. Accordingly, if for anyreason data stored in the text word context node 768 e indicates that aposition and/or size of the word “green” (or other word(s) associatedwith node 768 e) has changed in the electronic document 800, the links818 and 820 will allow the application program to detect that, ifpossible, it should adjust the rendering of the strikeout and/or adjustits size (if possible) to a location, spatial position, and/or size ofthe word stored in context node 768 e in the changed electronicdocument. Again, any suitable linking arrangement between nodes or anysuitable data representing a link may be used without departing from theinvention.

FIGS. 9A and 9B illustrate another example of a type of annotation andfurther demonstrate association or linking annotations with more than asingle text word. In the example illustrated in FIGS. 9A and 9B, theelectronic document 900 again includes the sentence “Today the sky isgreen,” but in this instance, a user of a pen-based computing system hasannotated the document 900 using electronic ink to circle the words “isgreen” (the circle or “container” type annotation is shown at referencenumber 902 in FIG. 9A). FIG. 9B illustrates an example hierarchical datastructure 910 corresponding to this composite electronic document 900once it is fully parsed (because the specific context nodes for much ofFIG. 9B correspond to the context nodes present in FIG. 7B, the samereference numbers as those present in FIG. 7B are used in FIG. 9B, andthe duplicative explanation is omitted). In this instance, the parseragain will note the presence of data in the electronic document 900relating to the annotation 902, and it will classify this data as anelectronic ink drawing (ink drawing node 912). Additionally, based onthe location and position of the ink drawing stroke(s) with respect tothe content of the underlying typewritten text in the document 900, theparser will recognize and classify the annotation as a “container”annotation and generate an ink container node 914 in the data structure910. Additionally, the parser will store all stroke data correspondingto the actual ink stroke(s) of the container annotation in one or morestroke leaf nodes 916 (or alternatively, as a property of the inkcontainer node or another appropriate node).

As was the case with respect to the underline and strikeout annotationsdescribed with respect to FIGS. 7A through 8B, the container annotationmay be maintained with the words “is green,” should these words move forany reason. Again, this may be accomplished, for example, by saving datain the data structure 910 to indicate that the ink container contextnode 914 (the “source” context node in this example) is linked to eachof the text word nodes 768 d and 768 e for the words “is green”(“destination” context nodes in this example), as illustrated in FIG. 9Bby arrows 918 a and 918 b. Additionally, data may be saved in the datastructure 910 to indicate that the text word nodes 768 d and 768 e arelinked by the container node 914, as indicated by arrows 920 a and 920 bin FIG. 9B. This link is a “containment” type link. Accordingly, if forany reason data stored in the text word context nodes 768 d and 768 eindicate that a position and/or size of the words “is green” (or otherword(s) associated with these context nodes) have changed in theelectronic document 900, the links 918 a, 918 b, 920 a, and 920 b willallow the application program to detect that, if possible, it shouldadjust the rendering of the container annotation and/or its size to alocation, spatial position, and/or size of the words stored in contextnodes 768 d and 768 e in the changed electronic document. Additionally,if a user adds words between the words “is” and “green,” or if the wordsor characters are removed or changed in any manner, the applicationprogram may alter the size and/or location of the container annotationto accommodate these changes. Again, other linking arrangements or dataindicating a link may be stored without departing from the invention.

FIGS. 10A and 10B illustrate another type of annotation commonly used,specifically a “margin comment” type annotation. In this example, asillustrated in FIG. 10A, a user has annotated an electronic document1000 containing the sentence “Today the sky is green” with an electronicink margin comment 1002 stating: “it's not green!”Notably, in thisinstance, as shown in FIG. 10B, the data structure 1010 associated withthe typewritten text has changed because this text is present in twolines in electronic document 1000 (rather than the single line shown inFIGS. 7A, 8A, and 9A). Accordingly, the data structure 1010 has two linenodes 1012 and 1014, and the first line node 1012 includes text wordnodes 768 a and 768 b (associated with the words “Today” and “the”) andsecond line node 1014 includes text word nodes 768 c, 768 d, and 768 e(associated with the words “sky,” “is,” and “green.”).

Once the composite electronic document 1000 is fully parsed, the parserwill recognize the annotation 1002 as containing electronic ink text,and it will classify this annotation (e.g., due to its location in themargin of the document 1000) as a “margin comment” type annotation.Accordingly, the parser will generate an appropriate context node 1016for a margin comment. Because this margin comment 1002 contains onlyelectronic ink text, the parser further generates a paragraph node 1018,two line nodes 1020 and 1022, and the appropriate ink word nodes 1024,1026, 1028 and stroke nodes 1030, 1032, and 1034 associated with theelectronic ink's hierarchical structure (as previously noted, optionallyand alternatively, the ink stroke data may be stored as properties ofthe ink word node(s) and/or the line nodes may be omitted from the datastructure 1010).

A different linking relationship is illustrated in the example of FIGS.10A and 10B. Specifically, in this example, based on the location andorientation of the margin comment 1002 with respect to the page marginsand the underlying document content, the parser will save data in thedata structure 1010 indicating that the paragraph node 1018 associatedwith the margin comment 1002 (the “source” context node in this example)is linked to the paragraph node 764 associated with the typewritten text(the “destination” context node in this example), as illustrated in FIG.10B by arrow 1036. Additionally, the parser will save data in the datastructure 1010 to indicate that the paragraph node 764 associated withthe typewritten text is linked by the paragraph node 1018 of the margincomment 1002, as illustrated by arrow 1038. This is an “anchored” typelinking arrangement in which the ink paragraph is anchored to the textparagraph. In this manner, wherever the typewritten paragraph moveswithin electronic document 1000, the links 1036 and 1038 will allow theapplication program to detect that, if possible, it should move themargin comment 1002 to remain in the margin adjacent to the linkedtypewritten paragraph, even, optionally, if additional lines and/orwords are added to the paragraph, and/or if lines and/or words areremoved from the paragraph, and/or if other changes are made within theparagraph or electronic document 1000. Of course, other linkingarrangements or data associated with the links may be stored withoutdeparting from the invention. For example, the margin comment node 1016may be linked to one or more individual text word nodes of thetypewritten paragraph, such as the first text word node 768 a.

FIGS. 11A and 11B illustrate a somewhat more complex example of anannotation recognizable by systems and methods according to at leastsome examples of this invention. In the illustrated example, theelectronic document 1100 again includes the phrase “Today the sky isgreen,” but in this instance, the user has annotated the electronicdocument 1100 using a combination of different annotation types.Specifically, the user has drawn a container type annotation 1102encircling the word “green,” a margin comment type annotation 1104containing the electronic ink word “Blue!,” and a connector typeannotation 1106 (e.g., an arrow in this example) pointing from thecontainer type annotation 1102 to the margin comment annotation 1104.

Because of the relative position and spatial orientation of the variousannotation types with respect to the underlying document, thetypewritten document text, and the document's margins, the parser systemaccording to at least some examples of this invention will recognize thevarious annotation types, their content, and their relationship to oneanother and to the electronic document typewritten text as generallydescribed above. An example hierarchical data structure 1110 forelectronic document 1100 generated by the parser is shown in FIG. 11B.Because the hierarchical structure for the typewritten text is the sameas that described above in FIG. 7B, the same reference numbers are usedfor this structure in FIG. 11B, and the detailed explanation is omitted.Also, as illustrated in FIG. 11B, the node chain 1112 for the inkcontainer type annotation 1102 is similar to that illustrated in FIG.9B, and the node chain 1114 for the margin comment type annotation 1104is similar to that illustrated in FIG. 10B. Accordingly, detaileddescription of these node chains is not included.

To maintain the spatial position of the annotations with the appropriateportion and spatial location of the underlying text, various linksbetween the annotation nodes and with the appropriate text node areprovided by the parser and stored in the data structure 1110. In theillustrated example, the ink container node 1116 (the “source” contextnode here) is linked to the text word node 768 e of the word that itcontains (i.e., the “destination” node corresponding to the word “green”in this example), as illustrated in FIG. 11B by arrow 1118. Similarly,data is stored in the data structure 1110 indicating that text word node768 e is linked by ink container node 1116, as indicated in FIG. 11B byarrow 1120. This is a “container” type linking arrangement.

As noted above, the parser according to this example of the inventionfurther recognizes that the electronic document 1100 includes an inkdrawing 1106 corresponding to an ink connector (i.e., the arrow betweenthe container annotation 1102 and the margin comment annotation 1104 inthis example). This connector annotation 1106 is stored in the datastructure 1110 as an ink drawing (represented by ink drawing node 1122),which contains a node indicating the annotation type (an ink connectornode 1124, in this example), which further includes data indicating thestroke or strokes making up the connector (e.g., in stroke node(s) 1126or in a property associated with ink connector node 1124 (or anothersuitable node)). Furthermore, information is stored in the datastructure 1110 to indicate that the ink connector node 1124 (the“destination” node in this example) is pointed from the ink containernode 1116 (the “source” node in this example). This link (a “pointsfrom” type link) is represented in FIG. 11B by arrow 1128. Additionally,the data structure 1110 further includes data to indicate that the inkconnector node 1124 (the “source” context node in this example) islinked to the ink word node 1132 (the “destination” context node in thisexample). This link (a “points to” type link) is represented in FIG. 11Bby arrow 1134. Alternatively, the ink connector node 1124 could belinked with any one of the ink line node, the ink paragraph node, or themargin comment node of node chain 1114 without departing from theinvention. With the specific links described above, the data structure1110 indicates that the ink connector 1106 points from the circledrawing 1102 and points to the ink word, as illustrated in FIG. 11A.These various links allow the application program to detect theassociation between the underlying document and the various annotationcomponents. Then, if possible, the application program can move theannotation elements to appropriately correspond to movements in theunderlying document. Any suitable linking arrangement or data associatedwith a link may be used without departing from the invention.

FIGS. 12A and 12B illustrate another example of a commonly usedannotation feature. In this example, as illustrated in FIG. 12A, theelectronic document 1200 again includes the sentence “Today the sky isgreen,” but in this instance, a user of a pen-based computing system hasannotated the document 1200 using electronic ink to place a star or anasterisk near the first word of the sentence (the annotation is shown atreference number 1202). FIG. 12B illustrates an example hierarchicaldata structure 1210 corresponding to this composite electronic document1200 once it is fully parsed (because the context nodes for much of FIG.12B correspond to the context nodes present in FIG. 7B, the samereference numbers as those present in FIG. 7B are used in FIG. 12B, andthe duplicative explanation is omitted). In this instance, the parserwill note the presence of electronic ink data relating to theannotation, and it will classify this data as an ink drawing (inkdrawing node 1212). Additionally, based on the ink stroke shape as wellas the location and position of the ink stroke(s) of the annotation 1202with respect to the content of the underlying document 1200 (e.g., alongside the line of typewritten text), the parser will recognize theannotation as an “asterisk,” “bullet,” or anchor type annotation andgenerate an asterisk node 1214. Additionally, the parser will store allstroke data corresponding to the actual ink stroke(s) of the asterisk inone or more stroke leaf nodes 1216 or in a property of the asterisk node(or some other node).

In this example, the asterisk type annotation 1202 may be maintainedwith the entire line of typewritten text wherever that line appears inthe electronic document 1200, should the typewritten text move for anyreason. This may be accomplished, for example, by storing data in thedata structure 1210 to indicate that the asterisk context node 1214 (the“source” context node in this example) is linked to the text line node766 (the “destination” context node in this example), as illustrated inFIG. 12B by arrow 1218, and by storing data to indicate that the textline node 766 is linked by the asterisk node 1214, as indicated by arrow1220. Accordingly, if for any reason data stored in the text linecontext node 766 indicates that a position or location of the line haschanged in the electronic document 1200, the links 1218 and 1220 willallow the application program to detect that, if possible, it shouldadjust the rendering of the asterisk to a location and/or spatialposition corresponding to the rendering of data associated with thecontext node 766 in the changed electronic document. Alternatively, ifdesired, the parser could tie the asterisk node 1214 (or other suitablenode associated with the asterisk annotation) to the paragraph node 764or one of the individual word nodes (e.g., word node 768 a) withoutdeparting from the invention. Also, if desired, the ink drawing node1212 may be the source node anchored to the line node 766 (or othersuitable node corresponding to the typewritten text in this example).Any suitable linking arrangement or data representing a link may be usedwithout departing from the invention.

A “flow chart” type of linked annotation is illustrated with the aid ofFIGS. 13A and 13B. In this example, the electronic document 1300includes a flowchart, which optionally may be included as part of anannotation in an overall larger electronic document. As illustrated inFIG. 13A, the annotation or flow chart includes a first ink entry 1302(the letter “A” in this example) encircled or enclosed by a firstcontainer annotation 1304 and a second ink entry 1306 encircled orenclosed by a second container annotation 1308. Additionally, aconnector annotation 1310 (an arrow in this example) extends from thefirst container annotation 1304 to the second container annotation 1308.It should be appreciated, however, that relationships between documentelements can be represented in alternate ways other than links. Forexample, these relationships can be represented in the structure of thedata tree itself through, e.g., the use of container nodes that containassociated document elements.

FIG. 13B illustrates an example data structure 1320 that may beassociated with the flow chart annotation of the electronic document1300 in FIG. 13A once fully parsed. In this example data structure 1320,a root node 1322, which may correspond to all or some portion of theelectronic document 1300, is provided as the parent node to nodes withinthe flow chart type annotation. A first context node relating to thespecific annotation structures is the ink drawing node 1324corresponding to the ink container 1304. An ink container node 1326 isprovided as a child node to ink drawing node 1324, and the specificstroke(s) associated with the ink container annotation 1304 are storedin leaf node(s) 1328 or as properties to the ink container node 1326 (orother node).

As noted above with respect to FIG. 13A, the annotation further includeselectronic ink text corresponding to the letter “A” 1302. As common withother electronic ink text described above, the electronic ink associatedwith this ink text is stored in the hierarchical data structure 1320 asa paragraph node 1330, which contains a line node 1332, which containsan ink word node 1334, which optionally contains one or more leaf nodes1336 corresponding to the individual strokes in the ink text annotationor a property including the stroke data. Information stored in the datastructure 1320 indicates that the ink container node 1326 of thecontainer annotation 1304 (the “source” node) is linked to the paragraphnode 1330 of the letter “A” (the “destination” context node), asillustrated in FIG. 13B by arrow 1338. Alternatively, if desired, theink word node 1334 or line node 1332 could serve as the destinationnode. Additionally, information stored in the data structure 1320 alsoindicates that the paragraph node 1330 is linked by the ink containernode 1326, as indicated in FIG. 13B by arrow 1340. Because the datastructure for the ink container 1308 and the letter “B” 1306 of theannotation in this example share the same general structure as that forthe ink container 1304 and the letter “A” 1302, including the samegeneral linking structure, the various nodes in the data structure 1320for the letter “B” 1306 and its associated container 1308 share the samereference numbers as those associated with the letter “A” and itscontainer, but the letter “b” follows the reference numbers for inkcontainer 1308 and ink word 1306 in FIG. 13B. Of course, the varioushierarchical arrangement and linking structure or linking data coulddiffer from that specifically described above without departing from theinvention.

The annotation further includes a connector annotation 1310, representedin the data structure 1320 by an ink drawing node 1342. As describedabove in connection with FIG. 11B, the data structure for an ink drawingrepresenting an ink connector annotation further may include an inkconnector node 1344, which further may include one or more properties orleaf node(s) 1346, that include data associated with the specificstroke(s) that make up the connector 1310. To complete the annotationdata structure of this example, data associated with the ink connectorannotation 1310 (the source node) is linked to data associated with thetwo container annotations 1304 and 1308 (destination nodes).Specifically, as shown in the example of FIG. 13B, information is storedin the data structure 1320 to indicate that the ink container node 1326is linked to the ink connector node 1344 (represented by arrow 1348) asa “points from” annotation type. Additionally, information is stored inthe data structure 1320 to indicate that the ink connector node 1344 islinked to the ink container node 1326 b (represented by arrow 1352) as a“points to” annotation type. In this manner, data stored relating to thelinks indicates that the connector 1310 points from the circle container1304 to the circle container 1308, as illustrated in FIG. 13A. Thus, theexistence of the various links will allow movement of one part of theannotation in the electronic document 1300 to be followed by the otherparts of the annotation, to thereby keep the annotation intact even ifthe electronic document 1300 changes in some manner. Of course, thisoverall structure also could be linked to some underlying documentelement as described above, without departing from the invention.

Similarly, an annotation may involve two enclosers connected by aconnector with a written comment, such as, e.g., “switch these!” If onepart of the annotation is moved, it might need to move independently ofthe other part of the annotation, such as when words are insertedbetween the two enclosers. The links between the context nodesrepresenting the electronic ink annotations and the nodes representingthe non-ink content can be used by a software application to relocatethe pieces of the annotation and then tie them back together when thepositioning operation is complete.

FIGS. 14A and 14B illustrate another example of an electronic document1400 having a flow chart type annotation or ink structure. In thisexample, the electronic ink annotation for the letter “A” 1402 isconnected to electronic ink annotations for the letters “B” 1404 and “C”1406, with electronic ink connectors 1408 and 1410 between the letters“A” and “B” and “A” and “C,” respectively.

An example data structure 1420 for electronic document 1400 afterparsing is illustrated in FIG. 14B. Data relating to the entireelectronic document or some portion thereof may be stored in the parentroot node 1422. Data corresponding to the electronic ink words “A,” “B,”and “C” have the same paragraph node (1424 a, 1424 b, 1424 c), line node(1426 a, 1426 b, 1426 c), ink word node (1428 a, 1428 b, 1428 c), andstroke node(s) (1430 a, 1430 b, 1430 c) structure as used in severalfigures above. Repetitive description of these nodes will be omitted.Likewise, the ink connectors have the ink drawing node (1432 a, 1432 b),ink container node (1434 a, 1434 b), and stroke node(s) (1436 a, 1436 b)structure used in FIGS. 11B and 13B above, so the repetitive descriptionis omitted. Of course, variations in these specific data structures,including the possible variations described above, may be used withoutdeparting from the invention.

To complete the annotation data structure of this example, dataassociated with the ink connector annotation 1408 is linked to dataassociated with the two ink word annotations 1402 and 1404 that itconnects, and data associated with ink connector annotation 1410 islinked to data associated with the two ink word annotations 1402 and1406 that it connects. Specifically, as shown in the example of FIG.14B, information is stored in the data structure 1420 to indicate thatthe ink drawing node 1432 a (the “source” node) “points to” the ink wordnodes 1428 a and 1428 b (as represented by arrows 1438 and 1440,respectively). Similarly, information is stored in the data structure1420 to indicate that the ink drawing node 1432 b (the “source” node)“points to” the ink word nodes 1428 a and 1428 c (as represented byarrows 1442 and 1444, respectively). The ink word nodes 1428 a, 1428 b,and 1428 c serve as “destination” nodes. Because of the various links,movement of one part of the annotation in the electronic document 1400can be followed by other parts of the annotation, to thereby keep theannotation intact or linked, even if the electronic document 1400changes in some manner. Also, this annotation can be linked with one ormore other elements in the electronic document, such as typewrittentext, drawings, images, etc., without departing from the invention.

FIGS. 15A through 15C illustrate examples of an electronic document 1500and example data structures that include an electronic ink annotation inthe form of a table having plural rows and columns. Specifically, asillustrated in the example of FIG. 15A, the electronic document 1500includes a table 1502 with two rows and two columns (making up fourtotal cells), and each cell of the table is made up of electronic inkborders and contains electronic ink text input.

An example data structure 1510 for the electronic ink table 1502illustrated in FIG. 15A, after complete parsing, is shown in FIG. 15B.In this example, data structure 1510 includes a root node 1512, whichmay correspond to all or some portion of the electronic document 1500.Under the root node 1512, relevant data relating to the table is storedin the table node 1514. This may include, for example, data indicatingthe table size, table position, number of rows, number of columns,bounding box size, and the like. Under the table node 1514, separate rownodes are provided for each row of the table (in this example, asillustrated in FIG. 15B, two row nodes 1516 and 1518 are provided). Eachrow node of this example data structure further includes one or morecell nodes (in the illustrated example, row node 1516 includes two cellnodes 1520 and 1522, while row node 1518 includes two cell nodes 1524and 1526). Because each cell of this example contains electronic inktext data, the remainder of this example hierarchical data structure1510 has the familiar paragraph node, line node, ink word node, andstroke node(s) described in detail above. Of course, the table cellscould contain one or more other types of data in addition to and/or inplace of the electronic ink data, including, for example, typewrittentext data and/or any of the various data types described in detail abovewith respect to FIG. 6I, without departing from this invention. Asanother alternative, instead of row nodes 1516 and 1518, the datastructure may include column nodes, which may then include cell nodes,paragraph nodes, etc., as shown in FIG. 15B. The ink strokes that makeup the actual table may be stored, for example, as a part of table node1514 (e.g., as properties associated with that node), as an ink drawingnode that depends from the table node 1514 (with the associated strokesstored thereunder), and/or at any other suitable location in the datastructure 1510.

An alternative example data structure 1530 for the electronic document1500 including table 1502 is shown in FIG. 15C. In this example, theroot node 1512; table node 1514; row nodes 1516 and 1518; and cell nodes1520, 1522, 1524, and 1526 are the same as those illustrated in FIG.15B. However, rather than include the electronic ink text data as childnodes under the various cell nodes 1520, 1522, 1524, and 1526, theparagraph nodes 1528 a, 1528 b, 1528 c, 1528 d of the electronic inktext data (or any other suitable or desired data structure) is linked toits respective cell nodes 1520, 1522, 1524, and 1526, as shown in FIG.15C by arrows 1530 a, 1530 b, 1530 c, and 1530 d, respectively. The cellnodes in this example may serve as container type “source” nodes for theink words contained therein, and the ink paragraph, line, or word nodesserve as “destination” context nodes. Because of the various links,movement of one part of the table annotation in the electronic document1500 can be followed by other parts of the annotation, to thereby keepthe table annotation intact or linked, even if the electronic document1500 changes in some manner. The table also can be linked to some othernodes present based on the underlying electronic document. Again, as analternative, row nodes 1516 and 1518 may be replaced with column nodesthat contain the various cell nodes, without departing from theinvention. Also, the ink strokes that make up the actual table may bestored at any location without departing from the invention, forexample, as a part of table node 1514 (e.g., as properties associatedwith that node), as an ink drawing node that depends from the table node1514 (with the associated strokes stored thereunder), and/or at anyother suitable location in the data structure 1510.

Of course, the various figures relating to the various exampleannotation types described above merely describe examples of possibleannotation types, use of annotations, and information that can beincluded within the annotations. Those skilled in the art will recognizethat many modifications and changes can be made without departing fromthe invention. For example, annotations may contain many different typesof data (such as electronic ink text, drawings, images, typewritten textand images, etc.), in many different combinations and permutationswithout departing from the invention.

Additionally, various linking schemes are described in conjunction withthe various data structures described above. Such linking schemes ortechniques are merely examples of the manner in which the various datanodes may be linked together. Any suitable linking arrangement or dataassociated with a link may be stored without departing from theinvention. For example, it may be possible to represent each node withan individual identifier (such as a “globally unique identifier,” orGUID) and represent the links using GUID pairs (or more). As anotheralternative, a single link may be used to link nodes rather than thedouble linking arrangement described with respect to some examplesabove. As another possible alternative, if necessary or desired, a nodemay be linked with itself (self-linking, e.g., where the source node andthe destination node are the same node). Those skilled in the art willrecognize that any suitable manner of linking or associating variousdata sets with one another may be used without departing from theinvention.

Analysis of Ink

Various example techniques for analyzing electronic ink in an electronicdocument in accordance with examples of the invention will now bedescribed. In particular, FIGS. 16A through 16E illustrate a flowchartshowing steps of analyzing a document according to various examples ofthe invention. FIGS. 17-26 then illustrate the relationships betweendifferent components employed during the analysis process.

Turning now to FIG. 17, this figure illustrates a software application1701. The software application 1701 maintains a document 1703, which mayinclude both electronic ink data 1705 and non-ink data 1707, such astypewritten characters or images. As discussed in detail above,properties of both the electronic ink data 1705 and the non-ink data1707 may be described by a hierarchical data structure, such as a tree.To begin the analysis of the electronic ink, in step 1601 the softwareapplication 1701 creates such a data structure, identified as theanalysis context object 1709 in FIG. 17.

FIG. 18 illustrates an example tree 1801 of the type that might beincluded in the analysis context object 1709. The tree 1801 includes aroot node 1803, and a paragraph node 1805. The paragraph node 1805corresponds to a paragraph of electronic ink text that, for example, mayhave been previously identified from an earlier analysis process. Theparagraph node 1805 is connected to two line nodes 1807 and 1809, whichrepresent two lines in the paragraph of electronic ink text. Line node1807 is, in turn, associated with two word nodes 1811 and 1813. Eachword node 1811 and 1813 corresponds to a word in the line of electronicink text represented by the line node 1807. Word node 1811 contains inkstroke data 1815 and ink stroke data 1817. Thus, stroke data 1815 and1817 correspond to text electronic ink strokes making up the wordrepresented by the word node 1811. Similarly, word node 1813 containsink stroke data 1819 and ink stroke data 1821, which correspond to textelectronic ink strokes making up the word represented by the word node1813. The tree 1801 also includes stroke data 1823-1827 that isassociated only with the root node 1803. This ink data 1823-1827represent new ink strokes that have not been classified or associatedwith another ink stroke or other document element.

Thus, rather than storing the strokes in individual stroke nodes,various nodes may have an associated “strokes” property that stores datacorresponding to the strokes associated with the node. For example: (a)unclassified context nodes may contain one or more “strokes” propertieshaving one or more strokes that need to be analyzed; (b) ink word nodesmay contain one or more “strokes” properties containing one or morestrokes that make up an ink word; (c) drawing nodes may contain one ormore “strokes” properties containing one or more strokes that make up adrawing; and (d) bullet nodes may contain one or more “strokes”properties containing one or more strokes that make up the bullet in alist item. Of course, with alternate implementations of the invention,individual stroke nodes can be used in the data tree to representindividual strokes of electronic, rather than associating ink strokeswith, e.g., a word node or drawing node.

While the tree 1801 shown in FIG. 18 includes ink strokes that havealready been organized into words, lines and paragraphs, it should beappreciated that the tree 1801 may contain only new ink strokes thathave not been classified or associated with another ink stroke ordocument element. For example, when a user initially enters electronicink into the document 1705, these initial ink strokes will not have beenanalyzed. It also should be appreciated that the tree 1801 isrepresentative only, and it is oversimplified for ease in understandingvarious aspects of the invention. For example, a line node typicallywill be associated with a plurality of word nodes, and each word nodemay contain stroke data for several ink strokes. It also should be notedthat, while the tree 1801 only includes ink-related nodes, the analysiscontext object 1709 may include nodes representing non-ink documentelements, such as images and typewritten text, as described in detailabove.

Returning now to FIG. 17, with some examples of the invention thesoftware application 1701 will create and maintain its own analysiscontext object 1709. For these software applications 1701, the softwareapplication 1701 can simply provide a reference to the analysis object1709. For these software applications 1701, however, the application1701 must include the mechanisms necessary to create, populate, andmaintain the analysis object. Some software developers, however, willnot want to go to the trouble of providing these mechanisms with theapplication 1701.

Accordingly, with other examples of the invention, however, the softwareapplication 1701 may instantiate another object to create the analysiscontext object 1709. For example, the software application 1701 mayemploy the ink analysis tool or other object to create and/or maintainthe analysis context object 1709. For example, a software application1701 may identify or provide unanalyzed ink data to the ink analysistool. Depending upon the instructions from the software application1701, the ink analysis tool may then create an analysis context object1709 representing the entire document 1703, or, alternately, just aparticular region (or regions) of the document that contain unanalyzedink identified by the software application 1701. With some softwareapplications 1701, the software application 1701 may thereafter maintainand update the analysis context object 1709, either by itself or usingservices provided by the ink analysis tool or another object. With stillother software applications 1701, the software application 1701 may notmaintain the analysis document object 1709, and instead have the inkanalysis tool or other object create a new analysis document object 1709when necessary.

Typically, the analysis context object 1709 will contain information ondocument elements for the entire document 1703. It also should be noted,however, that with some examples of the invention, the analysis contextobject 1709 may contain information for document elements in only aportion of the document 1703. That is, the analysis context object 1709may represent only document elements in a spatial area of the documentcontaining new or “dirty” ink or other data. If all of the documentelements in an area of a document, including electronic ink, havealready been analyzed, then these previously analyzed documents elementsmay not be included in the analysis context object 1709. As anotheralternative, the application program may maintain a separate analysiscontext object 1709 for each page or other subset of data relating tothe entire electronic document 1703.

Once the software application 1701 has created the analysis contextobject 1709, in step 1603 the ink analysis tool 1901 copies at least aportion of the analysis context object 1709, as shown in FIG. 19. Moreparticularly, if the analysis context object 1709 is not limited toregions containing new ink and/or other data, as described above, thenthe software application 1701 will designate the regions of the document1703 that contain new ink and/or other data that should be analyzed. Thesoftware application 1701 then invokes the ink analysis tool 1901 tocopy the portion of the analysis context object 1709 corresponding tothe designated region of the document 1703. (Of course, if the analysiscontext object 1709 is already limited to describing regions thatcontain new ink, then the ink analysis tool 1901 may copy the entireanalysis context object 1709.)

While an application program 1701 will know which ink has not previouslybeen analyzed, it might not know which portion(s) of its electronicdocument 1703 (e.g., previously analyzed ink, underlying data in thedocument structure, etc.) affects the new ink (and hence, whichportion(s) to present to the ink analysis tool 1901). Therefore, in atleast some examples of the invention, the application program 1701 willmake large sections of the electronic document 1703 available to the inkanalysis tool 1901 through the analysis context object 1709. Theapplication program 1701 leaves it up to the ink analysis tool 1901 todetermine the information actually needed from the application program1701 via the analysis context object 1709.

In response to the call to analyze the new data, the ink analysis tool1901 makes various calls back to the analysis context object 1709, ifnecessary, in order to obtain the information from the analysis contextobject 1709 needed to analyze the new ink and/or other data in theregion designated by the software application 1701. For example, inaddition to the new ink and/or other data, the ink analysis tool 1901may query the analysis context object 1709 for information regarding inkand/or other data in the designated region that has already beenanalyzed, or for information regarding non-ink document elements in thedesignated region. The “designated region” may, in at least someexamples of the invention, correspond to data in the spatial area atand/or near the area containing the new ink or other data to beanalyzed.

Both previously analyzed ink and non-ink document elements, particularlythose elements located near the newly entered data to be analyzed, mayprovide a context that will improve the analysis of the unanalyzed inkor other data. As the ink analysis tool 1901 obtains the desiredinformation from the analysis context object 1709, the ink analysis tool1901 creates the document independent analysis context object 1903 withthe obtained information. Thus, the document independent analysiscontext object 1903 contains at least a subset of information containedin the analysis context object 1709, but it is independent from thedocument 1703. The use of this “call back” technique in the query basedspatial abstraction method described above makes it possible for the inkanalysis tool 1901 to efficiently obtain and analyze the necessary data,even for large documents. It should be noted, however, that theapplication 1701 can still restrict the content in the documentindependent analysis context object 1903 simply by not exposing contentto the analysis tool when requested.

It also should be noted that, while the ink analysis tool 1901 iscreating the document independent analysis context object 1903, thesoftware application 1701 should not change the analysis context object1709 (and it cannot allow other threads in the application programand/or other programs to change the analysis context object 1709 duringthis time period). That is, the software application 1701 should notenter new data into the document 1703 during this time period, andshould not allow other threads and/or application programs to do so. Theprocess of creating the document independent analysis context object1903 is relatively fast, however, and typically it will notsignificantly impact the operation of the software application 1701. Ifdesired, however, efforts to input data to the document 1703 may becached and entered into the system after the document independentanalysis context object 1903 is created.

Once the document independent analysis context object 1903 is created,all subsequent analysis of the unanalyzed ink and/or other data can beperformed on the document independent analysis context object 1903rather than the analysis context object 1709, allowing the softwareapplication 1701 to continue its normal operation without being delayedor stopped by the analysis of the unanalyzed ink and/or other data. Thesoftware application 1701 may even enter new electronic ink data 1705into the document 1703 (and into the analysis context object 1709)without interfering with the analysis of the unanalyzed ink in thedocument independent analysis context object 1903.

Accordingly, after the document independent analysis context object 1903has been created, in step 1605 the ink analysis tool 1901 creates aseparate analysis thread for analyzing the ink in the documentindependent analysis context object 1903. Accordingly, in step 1607, thesoftware application 1701 may resume control of the main processingthread, and can continue its normal operation. Then, in step 1609, theink analysis tool 1901 provides the document independent analysiscontext object 1903 to a first analysis process for analysis. Forexample, as shown in FIG. 20, the ink analysis tool 1901 may pass thedocument independent analysis context object 1903 to a parsing process2001 for parsing using the analysis thread. The parsing processadditionally may include one or more classification processes withoutdeparting from the invention (e.g., for classifying ink and/or otherdata into various different types, such as ink text, ink drawings,tables, charts, graphics, images, music, mathematics, drawingscontaining specialized symbols (such as electrical diagrams withresistors, capacitors, and the like), etc.). It should be noted that,with some examples of the invention, the ink analysis tool 1901 may makea copy of the document independent analysis context object 1903. As willbe explained in more detail below, a copy of the original form of thedocument independent analysis context object 1903 may be used toreconcile the analysis results of the analysis process with a currentstate of the document 1703.

After the first analysis process has analyzed the ink and/or other datain the document independent analysis context object 1903, the firstanalysis process returns the analysis results to the ink analysis tool1901, which in turn informs the software application 1701 in step 1611of the analysis results. For example, as shown in FIG. 21, if the firstanalysis process is a parsing process 2001, the parsing process returnsthe parsing results 2101 to the ink analysis tool 1901, which may thenpass a reference to the analysis results 2101 to the softwareapplication 1701 (e.g., by firing an event).

As will be explained in more detail below, with some examples of theinvention, the analysis results 2101 may be the document independentanalysis context object 1903 originally presented to the analysisprocess, but modified to include the new information produced by thefirst analysis process (e.g., the parsing results in this example). Withstill other examples of the invention, however, the analysis results2101 may be a modified copy of the document independent analysis contextobject 1903. By including the new information produced by the firstanalysis process in a copy of the document independent analysis contextobject 1903, the original document independent analysis context object1903 can be preserved for use, for example, by the reconciler and/or inother analysis processes as previously noted.

FIG. 22 illustrates an example of how a parsing process, such as theparsing process 2001, might modify the data tree 1801 to show the layoutchanges produced by the parsing operation. As seen in this figure, theparsing process 2001 has determined that the unanalyzed ink strokerepresented by the stroke data 1823 is part of the word represented bythe word node 1813. Accordingly, the parsing process has disassociatedthe stroke data 1823 from the root node 1803, and instead associated itwith the word node 1813.

The parsing process also has determined that the ink strokes representedby the unclassified stroke data 1825 and 1827 are part of a new word inthe line represented by the line node 1809 that had not been previouslyidentified. Accordingly, the parsing process 2001 has created a new wordnode 2201, and associated that word node 2201 with the line node 1809.The parsing process 2001 has then associated the stroke data 1825 and1827 to the new word node 2201. Thus, the parsing results 2101 describerelationships between the previously unanalyzed ink strokes and otherink strokes (or other document elements) identified by the parsingprocess 2001. Also, in addition to showing the relationship changesdetermined by the parsing process 2001, the parsing results 2101 alsomay include classification information determined by the parsing process2001. For example, each instance of ink stroke data 1823-1827 may bemodified to classify its corresponding ink stroke as a text ink strokerather than a drawing ink stroke. In at least some examples of theinvention, if desired, the parsing results 2101 may be represented inthe document independent analysis context object 1903.

As previously noted, the software application 1701 is able to enter newdata, including both new electronic ink data 1705 and new non-ink data1707, into the document 1703 while the first analysis process isanalyzing the document independent analysis context object 1903.Accordingly, the results of the first analysis process may no longer beapplicable to the current state of the document 1703. For example, whilea parsing process may be determining that an ink stroke is associatedwith a word, the user may have deleted the ink stroke from the document1703 altogether (e.g., along with the entire associated word or more).Accordingly, the analysis results 2101 must be reconciled with thecurrent state of the document 1703 in step 1613. An examplereconciliation process is illustrated generally in FIG. 23, and it willbe described in more detail below.

With some examples of the invention, the software application 1701 maymanually reconcile the analysis results 2101 with the current state ofthe document 1703. That is, the software application 1701 may sortthrough the analysis results 2101 to determine which of the results arerelevant to the document elements currently in the document 1703. Withother examples of the invention, however, the ink analysis tool 1901 mayprovide a reconciling function to reconcile the analysis results 2101with the current analysis context object 1709 (that is, the analysiscontext object 1709 reflecting the current status of the document 1703).As will be discussed in more detail below, the reconciliation functionof various examples of the invention will identify conflicts or“collisions” between the analysis results 2101 from the first analysisprocess and the analysis context object 1709 for the current state ofthe document 1703. The ink analysis tool 1901 will then update theanalysis context object 1709 based upon the analysis results in step1615, and create a new document independent analysis context object 1903from the reconciled analysis results in the analysis context object 1709in step 1617.

It should be noted that, while the ink analysis tool 1901 is reconcilingthe analysis results 2101 with the current analysis context object 1709,the software application 1701 should not change the analysis contextobject 1709 (and it should not allow the analysis context object 1709 tobe changed by other threads in the application program and/or any otherapplication program). That is, the software application 1701 should notenter new data into the document 1703 and/or it should not allow otherthreads and/or application program to enter new data into the document1703 until the reconciliation is completed. Like the process ofinitially creating the document independent analysis context object1903, the reconciliation process is relatively fast, and typically willnot significantly impact the operation of the software application 1701.If desired, however, attempted user input may be cached and enteredafter the reconciliation process is completed.

After the ink analysis tool 1901 has reconciled the analysis results2101 with the analysis context object 1709 for the current state of thedocument 1703, the ink analysis tool 1901 optionally may provide thereconciled analysis results to a second analysis process for furtheranalysis. For example, as shown in FIG. 24, the ink analysis tool 1901may provide reconciled parsing results 2401 to an ink recognitionprocess 2003 for recognition (e.g., for handwriting recognition of text,music, mathematical information, or other specialized data types). Inparticular, the ink analysis tool 1901 will again create a separateanalysis thread for performing the second analysis process in step 1619.Because the ink analysis tool 1901 creates this separate thread forexecuting the second analysis process, the software application 1701 canagain resume its normal operation in step 1621, and it may even acceptnew input data including new electronic ink data 1705.

Next, in step 1623, the ink analysis tool 1901 provides the reconciledresults 2401 from the first analysis process to the second analysisprocess. Once the second analysis process has started, the application1701 may start another execute of the first analysis process on newunanalyzed ink. Thus, multiple analysis processes may be runningconcurrently, so that, while the second analysis process is working onthe results of the first analysis process, the application 1701 canrestart the first analysis process to prepare the next set of analysisresults.

Advantageously, executing the analysis processes in parallel may improvethe operation of the software application 1701. For example, the parsinganalysis process is typically fast relative to a recognition analysisprocess, and parsing analysis results can be used to implement correctselection behavior and space-insertion behavior without the use ofrecognition analysis results. Thus, because the different analysisprocesses can execute in parallel, new ink that added to the document1703 does not have to wait for the recognition analysis process tofinish on the older ink data before it can be selected or have spaceinserted in it correctly. Further, various examples of the inventionaccomplish asynchronous ink analysis as to isolate applicationdevelopers as well as parser and recognizer algorithm developers frommultithreading issues, improving maintainability and simplifying thedevelopment process for both groups, and allows changes to interactionbetween analysis processes without changes to the application.

As noted above, the ink analysis tool 1901 may provide the reconciledanalysis results by creating a new document independent analysis contextobject 1903 from the analysis document object 1703 after it has beenupdated to include the relevant portions of the analysis results 2101.With other examples of the invention, however, the ink analysis tool1901 may simply update the original document independent analysiscontext object 1903 with the analysis results 2101 to reflect thecurrent state of the document 1703. Still further, the ink analysis tool1901 may simply provide the relevant ink data to be analyzed further tothe second analysis process.

Thus, various examples of the invention reconcile the results of a prioranalysis process with the current state of the document 1703 beforeexecuting a subsequent analysis process. It should be appreciated,however, that this intermediate reconciliation step may be omitted withsome examples of the invention. More particularly, with some examples ofthe invention, the results of an earlier analysis process may bedirectly provided to a subsequent analysis process, without reconcilingthose results with the current state of the document 1703. For example,if an ink classifier process is provided separate from the ink layoutanalyzer process, then the ink classified as handwritten text may beprovided to the ink layout analyzer process without an intermediatereconciliation step.

With either arrangement, after the second analysis process 2003 hascompleted analyzing the reconciled results 2401 from the first analysisprocess, the second analysis process 2003 returns its results 2501 tothe ink analysis tool 1901 as shown in FIG. 25. The ink analysis tool1901 then informs the software application 1701 of the results 2501 ofthe second analysis in step 1625.

As previously noted, the software application 1701 is able to enter newdata, including new electronic ink data 1705, into the document 1703while the second analysis process is analyzing the reconciled results2401 of the first analysis process. The results 2501 of the secondanalysis process thus may no longer be applicable to the current stateof the document 1703. Accordingly, the results 2501 of the secondanalysis process 2003 also must be reconciled with the current state ofthe document 1703 in step 1627. An example reconciliation process isillustrated generally in FIG. 26, and it will be described in moredetail below.

Again, with some examples of the invention, the software application1701 may manually reconcile the second analysis results 2501 with thecurrent state of the document 1703. Alternately, with other examples ofthe invention, the ink analysis tool 1901 may provide a reconcilingfunction to reconcile the analysis results 2101 with the currentanalysis context object 1709. This reconciliation function will identifyconflicts or “collisions” between the analysis results 2501 from thesecond analysis process and the analysis context object 1709 for thecurrent state of the document 1703, and the ink analysis tool 1901 willthen update the analysis context object 1709 based upon the analysisresults in step 1629. This process can then be repeated as necessary toanalyze new ink input or ink that was changed during the analysisprocesses.

From the foregoing discussion, it will be apparent that the ink analysistechniques according to various examples of the invention allowelectronic ink to be analyzed asynchronously from the softwareapplication 1701, allowing the software application 1701 to continue toaccept input data, including new electronic ink, during the analysisprocesses. It should be noted that, while the above discussion describesonly two analysis processes, any number of analysis processes can beconcurrently performed in parallel. For example, various implementationsof the invention may employ a first parsing process, a second parsingprocess, and a recognition process. In this manner, once each analysisprocess is completed, its results can be passed on to the next analysisprocess, and the first analysis process may be run again, concurrentlyand in parallel, on newly input ink.

Further, with various examples of the invention one or more analysisprocesses may be executed sequentially. For example, with some softwareapplications, a user may be able to designate a specific language for anink stroke or collection of strokes, such as English or Japanese. Thislanguage designation may then be included in the analysis context object1709 and the document independent analysis context object 1903. Basedupon the language designation, the ink analysis tool 1901 may routeelectronic ink designated as a first language to a recognition processtailored for that first language, and subsequently route electronic inkdesignated as a second language to a different recognition processtailored for that second language. In this same manner, input dataclassified and/or designated as other specific types may be sent toother specialized recognizers, such as recognizers for music, electricalsymbols, mathematical symbols, flow chart features, graphical features,etc.

Moreover, because the analysis processes do not need to be part of thesoftware application 1701, any desired analysis process can be used toanalyze electronic ink in the software application 1701. For example, asoftware application developer can develop and employ a parsing processor a recognition process that is particularly suitable for analyzing theelectronic ink input expected for the software application 1701.

Still other variations of these techniques may be employed by variousimplementations of the invention. For example, in some situations, itmay not be desirable for the software application 1701 to maintain aninternal document tree reflecting the relationship between the variousdocument elements in the document 1703. Instead, the softwareapplication 1701 may be intended only to employ simple state informationregarding electronic ink input. With these software applications 1701,the software application 1701 may omit creating an analysis contextobject 1709 that reflect the current state of the entire document 1703.Rather, the software application 1701 may create a purpose-specificanalysis context object 1709 that only contains information relevant tospecific ink input that the software application 1701 desires to haveanalyzed. By using a purpose-specific analysis context object 1709, thesoftware application 1701 can avoid the complexity of maintaining aninternal data structure corresponding to the state of the document 1703,while still being able to employ the desired analysis processes toanalyze ink within the document.

Also, while the foregoing description discusses the asynchronousanalysis of electronic ink, it should be noted that various examples ofthe invention may allow the ink analysis tool 1901 to synchronouslyanalyze ink. For example, some implementations of the invention mayallow a software application 1701 to instruct the ink analysis tool 1901to perform an immediate and synchronous analysis of electronic ink.Further, the synchronous analysis may be only for ink within a specificregion of the document 1703, or for the entire document 1703.

The Ink Analysis Tool

As discussed above, the ink analysis tool 1901 performs a variety offunctions to facilitate the processing of electronic ink. For example,according to various implementations of the invention, the ink analysistool 1901 receives information from the software application 1701designating one or more regions in the document 1703 with ink data to beanalyzed, queries the software application 1701 to obtain informationregarding those regions, and then constructs a document independentanalysis context object 1903 based upon the information. Further, theink analysis tool 1901 provides the document independent analysiscontext object 1903 to one or more analysis processes for analysis, andthen reconciles the results of the analysis process with the currentstate of the document 1703. The various processes may be performed usingseparate threads (as described above), via a thread pool, as separateprocesses, via separate machines in a cluster, or in any other suitableor desired manner, without departing from the invention.

According to different examples of the invention, a variety of softwareobjects and tools can be employed to implement the ink analysis tool1901 and perform these functions. With some examples of the invention,however, the ink analysis tool 1901 is implemented as an applicationprogramming interface (API). More particularly, according to someexamples of the invention, the ink analysis tool 1901 can be implementedas a group of software objects routines and related information that canbe called by the software application 1701 as needed to analyze ink inthe document 1703.

As will be appreciated by those of ordinary skill in the art, anapplication programming interface may be organized into categories or“classes” pertaining to software objects. An “object” is a collection ofstorable state values and executable behaviors. More particularly, anobject can maintain different types of state values, referred to as“fields” and “properties,” which can be associated with or retrieved bythe object. With respect to an outside software application or anothersoftware object, these properties may be read only (identified by theuse of the term “{get;}”), write-only (identified by the user of theterm “{set;}”), or both readable and writable (identified as “{get;set}”). An object may also execute tasks or “methods,” often at therequest or “call” of a software application or another object. Thus, anapplication programming interface may include various objects that canbe instructed by another software application to perform specific tasksor provide specific information upon request.

It should be noted that various examples of the invention may beimplemented to require that the software application 1701 provide onlythe minimum amount of information necessary to complete the desiredanalysis process. For this reason, some of the properties described indetail below may be discussed only as read-only (i.e., “{get;}”) orwrite-only (i.e., “{set;}”) properties, but may be both readable andwritable for various alternate implementations of the invention. Forexample, a property that defines “hints” which are to be used by ananalysis process to analyze electronic ink may be identified as aread-only property for situations where the software application 1701does not intend to use hints. This allows the object created by the InkAnalyzer to at least read this property, and determine that the value ofthis property is the default value of null (i.e., that no “hints” aredesired by the software application 1701). If, however, the softwareapplication 1701 desires to employ hints for ink analysis, then thisproperty would be both readable and writable to allow the softwareapplication 1701 to change the value of this property from the nullvalue, in order to specify the desired hints.

According to various examples of the invention, an API embodying animplementation of the ink analysis tool 1901 (referred hereafter to asan Ink Analysis API), may contain two core classes. The first class willbe referred to as the “Analysis Context” class, and the second class isthe “Ink Analyzer” class. The components of the “Analysis Context” classare used to create the analysis context object 1709. Accordingly, withvarious implementations of the invention for which the softwareapplication 1701 creates and maintains its own analysis context object1701, one or more of the components in this class may be omitted fromthe ink analysis tool. Instead, one or more of these components may beimplemented by the software application 1701 itself.

The components of the “Ink Analyzer” class are then used to create andemploy an object that provides the document independent analysis contextobject 1903 to an analysis process, determine when the analysis resultshave been generated, and reconcile the analysis results with the currentstate of the document 1703. These and other classes that may be includedin an Ink Analysis API according to various examples of the inventionwill be discussed in detail below.

Turning first to the Analysis Context class, this class is implementedby the host application 1701 to create the analysis context object 1703,which serves as a proxy view onto the internal document tree of thesoftware application 1701. Alternatively, as previously noted, if theapplication implements its own analysis context object, then one or morecomponents in this class may be omitted from the ink analysis tool 1901.As discussed above, the analysis context object 1703 contains allunanalyzed ink data, and the analysis context object 1703 is used toidentify which unanalyzed ink data should be analyzed. The analysiscontext object 1703 also contains information about previously analyzedink. This previously analyzed ink may be used to decide how thecurrently unanalyzed ink should be analyzed, and itself may be modifiedin the course of analyzing the unanalyzed ink. Further, the analysiscontent object 1703 contains information about non-ink content of thedocument 1703, which is used to properly classify ink as annotations tothe non-ink content.

According to various examples of the invention, the Analysis Contextclass includes a constructor which, when called by the softwareapplication 1701, creates the analysis context object 1709. This classmay also include various properties for the analysis context object1709, including the property entitled “Dirty Region {get;}.” The DirtyRegion property defines the portion of the document (and thus theportion of the analysis context object 1709) that contains unanalyzedink data. With various examples of the invention, the Dirty Region maydefine a disjoint area. The Dirty Region is specified as anAnalysisRegion, which is described more detail below, but which maysimply be a collection of rectangular areas in the document. If theDirty Region is empty, no analysis will occur. This class may furtherinclude a property for the analysis context object 1703 entitled“Margins {get;},” which declares the areas of a page in the document1703 that are considered margins. An analysis process that, for example,analyzes the layout and determines the classification of electronic ink,may use this property to help determine the classification of electronicink that is annotating non-ink content (e.g., ink in the margins).

Still further, the Analysis Context class may include a propertyentitled “Rootnode {get;},” which identifies the topmost or root contextnode in the analysis context object 1709. As discussed in more detailabove, this root context node contains, as child context nodes, allother context nodes objects for the given analysis context object 1709.It should be noted that, with various examples of the invention, theroot context node must be of the context node type “Root.” It shouldalso be noted that, with examples of the invention where the application1701 implements its own analysis context object 1709, the analysiscontext object 1709 may have other context nodes as siblings of the rootcontext node, but components of the Ink Analyzer class may be limited toconsidering context nodes contained by the root context node.

The Analysis Context class may additionally include the property“Analysis Hints {get;},” which returns an array of analysis hint objectsset by the software application 1701. As will be discussed in moredetail below, the analysis hint objects may contain any type ofinformation that may assist the analysis process. This information mayinclude, for examples, as factoids, guides, or a word list. It may alsoinclude information setting a language to be used for analysis,information designating the unanalyzed ink as handwritten text only ordrawing only, or providing any kind of guidance to the parsing process,such as identifying the ink as lists, tables, shapes, flow charts,connectors, containers and the like.

In addition to these properties, the Analysis Context class may alsoinclude various methods that may be called by, e.g., the softwareapplication 1701 to have the analysis context object 1709 execute atask. For example, the Analysis Context class may include a methodentitled “FindNode (Guid id).” Each node in the analysis context object1709 has a globally unique identifier (or GUID), and this method willlocate the node specified in the call anywhere in the analysis contextobject 1709. This lookup method should be implemented as efficiently aspossible, since this method may be called from many time criticaloperations.

Like the Analysis Context class, the Ink Analyzer class also defines apublic constructor that allows the software application 1701 to createan instance of the class (i.e., an ink analyzer object), along withvarious properties. For example, it may contain a property entitled“User Interface Context {get; set;},” which defines the processingthread to which the results of the analysis process are returned. Thisproperty allows the results to be synchronized to another object. Forexample, if this is set to the main form, parser results will be firedon the application main thread. It may also contain the property“AnalysisOptions AnalysisOptions {get; set;}”, which specifies variouscriteria that may be used for the analysis process. These criteria mayinclude, for example, enabling text recognition, enabling the use oftables, enabling the use of lists, enabling the use of annotations, andenabling the use of connectors and containers.

The Ink Analyzer class will include various methods. For example, thisclass may include a method entitled “AnalysisRegion Analyze ( ).” Thismethod starts a synchronous analysis process. Document element data ispassed into this method, which describes the current state of thedocument 1703 and indicates what ink in the document 1703 needs to beanalyzed. With some implementations of the invention, the documentelement data can be provided as the analysis context object 1709 (i.e.,AnalysisRegion Analyze (Analysis Context)), as noted above. Alternately,individual ink strokes may be passed to the analysis process, eitherusing a reference to the strokes (i.e., AnalysisRegion Analyze(Strokes)) or referenced as a property of the Ink Analyzer object (e.g.,InkAnalyzer.Strokes {get;set}) with no properties passed to the Analyzemethod.

Once the analysis process is complete, this method will return areference to the document independent analysis context object that hasbeen modified to contain the results of the analysis process. The methodalso returns an AnalysisRegion value (discussed in detail below)describing the area in the document where results have been calculated.

The Ink Analyzer class may also include a method entitled“AnalysisRegion Analyze(AnalysisContext, waitRegion).” This method isthe same as the synchronous Analysis Region Analyze ( ) method discussedabove, but it only has ink analyzed if results are needed in thespecified waitRegion area. More particularly, the call to this methodwill identify the analysis context object 1709 for the document 1703 andthe region of the analysis context object 1709 (referred to as the“waitRegion”) for which the analysis process should analyzesynchronously. With various examples of the invention, all other regionsof the analysis context object 1709 will be ignored, unless the analysisprocess needs to analyze content in those regions in order to completeits analysis of the waitRegion. As discussed above, the analysis contextobject 1709 passed with this method contains a property called the“DirtyRegion” which describes the areas of the document 1703 that needanalysis. By specifying a particular waitRegion, the softwareapplication 1701 may obtain the analysis results more quickly for onespecific region of interest, rather than having all of the ink data inthe document 1703 analyzed.

When either of these Analyze methods is called, every available analysisprocess will be executed. Also, because these Analyze methods aresynchronous calls, there is no need to execute the reconciliationprocess upon their conclusion, nor will an event fire once it iscomplete.

The Ink Analyzer class may also include a method entitled“BackgroundAnalyze(AnalysisContext).” This method starts the specifiedanalysis operation, but does so on a separate background analysisthread. Thus, this method will return control to the main processingthread almost immediately while the actual analysis operation completesin the background. In particular, this method will return a value of“true” if the analysis process was successfully started. Again, theAnalysisContext value passed in to the method identifies the analysiscontext object 1709 for the document 1703 and indicates what ink in thedocument 1703 needs to be analyzed. Once the analysis operation hascompleted on the background thread, a Results event is raised to allowthe software application 1701 to access to the results. The eventcontains the results and the reconcile method which is used toincorporate the results back into the analysis context object 1709 forthe current state of the document 1703 when the results are returned.

It should be noted that each of these three Analyze methods in turn callthe method “Clone” in an “Analysis Region” class, which will bediscussed in detail below. Using the “Clone” method, these Analyzemethods create the independent document analysis context object that issubsequently modified by the analysis process to show the analysisresults.

The Ink Analyzer class may also include a method entitled “Reconcile(AnalysisContext current, AnalysisResultsEventArgs resultArgs),” whichthe software application 1701 calls after receiving the results eventwhich was caused by calling the BackgroundAnalyze(AnalysisContext)method. The Reconcile method compares the analysis results contained inthe document independent analysis context object with the currentversion of the analysis context object 1709 maintained by the softwareapplication 1701. This method identifies the nodes that need to be addedand removed from the current version of the analysis context object1709, and identifies if any of the following properties of an existingnode has changed: its recognition results, its location, the ink strokesassociated with the node, or any other data associated with the resultsof the analysis operation. This method also writes these identifiedchanges to the current version of the analysis context object 1709. Thismethod is sensitive to the ordering of context node ordering, such asthe order of word context nodes on a line context node.

The analysis results (that is, the value of the propertyAnalysisResultsEventArgs) are passed back with this method, as theycontain a public results structure and a private results structure. Thepublic structure is returned so the software application 1701 canpreview the changes that will occur in the reconcile stage. The privatestructure is included to prevent the software application 1701 fromchanging any of the analysis results before the reconcile process.

The Ink Analyzer class may also include the methods entitled“Recognizers RecognizersPriority( )” and“SetHighestPriorityRecognizer(recognizer).” When ink needs to berecognized, the appropriate recognizer will be used based on languageand capabilities Accordingly, the Recognizers RecognizersPriority( )method returns the recognition processes in the order in which they willbe evaluated by the Ink Analyzer object. The order is determined persystem depending upon recognition processes are available, but can beoverridden for the software application 1701 by calling theSetHighestPriorityRecognizer(recognizer) on the Ink Analyzer object. TheInkAnalyzer will enumerate through this ordered list until anappropriate recognizer can be found. TheSetHighestPriorityRecognizer(recognizer) method raises the priority of arecognition process. By raising the priority of a particular recognitionprocess, that recognition process will be used if it matches the neededlanguage and capabilities of the current recognition operation. Inessence, the SetHighestPriorityRecognizer(recognizer) pushes thedesignated recognition process to the top of the list returned by theRecognizersPriority method.

The Ink Analyzer class may also contain a method entitled“AnalysisRegion Abort( ),” which may use an analysis context object as aparameter. This method allows for a foreground or background analysisoperation to be terminated early. This method returns an analysis regionthat describes the area that was being analyzed prior to the abort.Thus, if the software application 1701 intends to continue the analysisoperation at a later time, this region can be merged into theDirtyRegion of the analysis context object 1709 for the current state ofthe document 1703. Still further, the Ink Analyzer class may include anevent entitled “AnalysisResultsEventHandler,” which fires to theInkAnalyzer object as frequently as practical. More particularly, thisevent may fire between analysis processes and at least once every 5seconds. This event can be used to provide the application 1701 with anupdate as to the status of an ongoing asynchronous analysis process (orprocesses).

The Ink Analysis API may also include classes in addition to theAnalysis Context class and the Ink Analyzer class. For example, the InkAnalysis API according to various examples of the invention may includea Context Node class. This class may include various components relatingto the context nodes that make up the analysis context object 1709 andthe document independent analysis context object, such as the propertyentitled “ContextNodeType Type {get;}.” As will be appreciated by thoseof ordinary skill in the art, each context node has a type, and there isa specific set of rules that each type must adhere to. This includesrules such as, for example, what types of child context nodes areallowed and whether or not strokes may be directly associated to thecontext node or only via its child context nodes.

The possible types of context nodes may be defined in a ContextNodeTypesenumeration and may include (but are not limited to), for example, thefollowing types: An Inkannotation node, which represents ink dataannotating non-text data; an InkDrawing node which represents ink dataforming a drawing, an InkWord node, which represents ink data forming aword, a Line node, which contains one or more InkWord nodes and/orTextWord nodes for words forming a line of text; ListItem node, whichmay contain Paragraph, Image, or like nodes expected in a list; and aList node, which contains one or more ListItem nodes each describing anentry in the list. The node types may also include a NonInkDrawing node,representing a non-ink drawing image; an Object node, representing datanot covered by other values of the ContextNodeType enumeration; aParagraph node, which contains a one or more Line nodes corresponding tolines forming a paragraph; a Picture or Image node, representing apicture image; a Root node, which serves as the topmost node in ananalysis context object; a Table node, which contains nodes representingitems making up a table; a TextBox node, representing a text box; aTextWord node; and an UnclassifiedInk node, corresponding to ink datathat has not yet been classified. The node types may also include aGroup node, for groups of other nodes, an InkBullet node for bulletitems, a Row node for documents elements presented in a row of a table,and a Cell node for document elements presented in a cell of a table.

The Context Node class may also include the property entitled “GUID Id{get;},” which is a globally unique identifier for the current contextnode. In order to allow access to any desired context node, each contextnode within a single analysis context object must always have uniqueidentifier. This class may also include a property entitled“AnalysisRegion Location {get;},” which identifies the location in thedocument space where the relevant context node is actually positioned.As previously noted, an AnalysisRegion is a two-dimensional structuregrouping one or more possibly disjoint rectangle like structurestogether. This class may also include the property entitled“StrokeCollection Strokes {get;}”, which identifies the ink strokesassociated with the relevant context node. With various examples of theinvention, only leaf context nodes (such as Word, Drawing and Bulletnodes) are allowed by the Ink Analysis API to have strokes. The softwareapplication 1701 may use this property to reference the strokes at theleaf node level by all ancestor context nodes (e.g., the root node wouldcontain a strokes reference to all strokes in the relevant analysiscontext object.)

Further, this class may include the property entitled “ContextNodeParentNode {get;},” which identifies the parent context node containingthe relevant context node. With various examples of the invention,context nodes are always created to depend from a parent context node,with the Root context node being a static member of an analysis contextobject. This class may also include the property “ContextNode[ ]SubNodes {get;}” which identifies all context nodes that are directchildren of the relevant context node. That is, this property will onlyidentify those children context nodes down one level in the analysiscontext object. For example, the value of this property for a Paragraphcontext node will only identify the line context nodes contained by theParagraph node, and not the word context nodes that are children of theline context node.

This class may also include the property entitled “RecognitionResultRecognitionResult {get;},”which provides the recognition result ascalculated by the relevant recognition analysis process or processes, asthe RecognitionResult can represent more than one line of text from inmore than one language. The Recognition Result is available for everycontext node in the document independent analysis context object eventhough the RecognitionData property (discussed in more detail below)which is set by the recognition analysis process and is used to createthe RecognitionResult object might only be set at one level of thecontext node tree to avoid duplication of data. If the node does nothave a RecognitionData associated with it, it will either merge therecognition results of all of its subnodes or extract the recognitionresult from its parent. This class may also include the propertyentitled “Stream RecognitionData {get; set;},” which is the persistentform of the RecognitionResult value. Again, the recognition analysisprocess produces the Stream RecognitionData value that is set on therelevant context node. The RecognitionResult object is then constructedbased on this value.

The Context Node class may further include a property entitled“ContextLink[ ] Links {get;},” which provides an array of ContextLinkobjects. A ContextLink object describes an alternative relationshipbetween two context nodes. While context nodes typically have aparent-child relationship with other context nodes, a ContextLink allowsfor an alternative relationship between context nodes. For example, aContextLink may allow for a connection between two context nodes,anchoring of one context node to another context node, containment ofone context node by another context node, or a desired type of linkdefined by the software application 1701. ContextLinks may be added tothis array by calling the AddLink method, discussed in more detailbelow. Similarly, ContextLinks may be removed from this array by callingthe DeleteLink method, which also is discussed in more detail below.

Still further, this class may include the properties “IsContainer{get;}” and “IsInkLeaf {get;}.” The property IsContainer {get;} has thevalue of “true” if the relevant context node is not a leaf context node(that is, if the relevant context node contains children context nodesand is thus considered a container context node), and has the value of“false” otherwise. The IsInkLeaf {get;} property has the value of “true”if the current context node is not a container context node, and has avalue of “false” otherwise. That is, if the current context node doesnot contain any children context nodes, it is considered a leaf contextnode. It should also be noted that, with various examples of theinvention, an InkLeaf context node is expected to contain references tostroke data, whereas container context nodes do not have thisrestriction. Container context nodes may or may not reference strokedata, as designated by the software application 1701.

The Context Node class may also contain the property “RectRotatedBoundingBox {get; set;}.” The value of this property iscalculated by a layout and classification analysis process. If the inkdata associated with the relevant context node is written at an angle,then the bounds for the context node will still be horizontally aligned.The value of the RotatedBoundingBox property, however, will be alignedto the angle at which the ink data associated with the relevant contextnode was written. Still further, this class may include the property“ReClassifiable {get;},” which informs the InkAnalyzer if it is allowedto modify the values of the relevant context node.

In addition to these properties, the Context Node class may also includevarious methods. For example, this class may include a method entitled“ContextNode CreateSubNode(ContextNodeType type).” This method allowsthe creation of a child context node of a particular type. With variousexamples of the invention, this method may only allow valid child typesof the relevant context node to be created, thereby preventing malformeddata structures from being created. For example, this method may onlyallow a Line context node to create Ink Word and TextWord child contextnodes). This class may also contain a method entitled “voidDeleteSubNode(ContextNode node),” which deletes the referenced childcontext node from the relevant analysis context object. It should benoted, however, that with various examples of the invention, if thereferenced context node still contains strokes or child context nodes,then this method should fail. Also, if the reference context node is nota direct child of the relevant context node, then this method shouldfail. It should be noted that, if a software application 1701 implementsits own analysis context object 1709 and in turn employs this method, itnot delete non-empty context nodes or context nodes that are not directchildren of the relevant context node to prevent malformed datastructures in the analysis context object 1709.

Still further, this class may include the method “ContextNode[ ]HitTestSubNodes(AnalysisRegion region),” which returns an array ofcontext node that are located in the specified region. It should benoted, however, that only the immediate children nodes of this elementare returned, not all descendants. The region is defined by theAnalysisRegion object which, as previously noted, may be a collection ofone or more rectangles. According to various examples of the invention,if any part of a context node's location intersects the specifiedregion, then that context node will be returned in the array. Thismethod is employed to, for example, create the document independentanalysis context object and to reconcile the analysis results with theanalysis context object corresponding to the current state of thedocument 1703. Thus, this method is frequently called, and should beoptimized for fast repeated access by the InkAnalyzer object.

The Context Node class may also contain a method entitled“MoveStroke(Stroke stroke, ContextNode destination).” This method movesthe association of a stroke from one leaf context node to another. Withvarious examples of the invention, this method is only used between leafcontext nodes. It may also include a method entitled“MoveSubNodeToPosition(int OldIndex, int NewIndex),” which reorders therelevant context node with respect to its sibling context nodes. Forexample, if the document 1703 has three words on a line, e.g., word 1,word 2 and word3, then their order is implied by the array of subnodesreturned from the parent context node. This method allows their order tobe changed, so that, relative to the relevant parent context node, word1 is specified to be the last word on the line by moving the contextnode for word 1 from position one to position three.

Still further, this class may include the method entitled“AddLink(ContextLink link),” which adds a new ContextLink object to thecurrent context node. With various examples of the invention, theContextLink object must contain a reference to the relevant context nodein order for the ContextLink to be successfully added to the array ofContextLinks associated to the relevant context node. It may alsocontain the method entitled “DeleteLink(ContextLink link).” This methoddeletes or removes the specified ContextLink object from the array ofContextLinks for the relevant context node. It should be noted that,with various examples of the invention, this method call alwayscompletes successfully, even if the ContextLink does not exist in thearray of ContextLinks associated with the relevant context node.

The Ink Analysis API may also include an Analysis Hint class. As withmany of the previously described classes, the Analysis Hint class mayinclude a constructor, entitled “AnalysisHint( ),” which initializes anAnalysis Hint object to an empty state. This class may also include anumber of properties, including a property entitled “AnalysisRegionLocation {get;}.” This property specifies the location in the document1703 (as an AnalysisRegion) to which the AnalysisHint is applicable. Forexample, if the document 1703 is a free form note with a title sectionat the top of the page, then the application 1701 could set anAnalysisHint for the title region to specify that a horizontal line ofink is expected in that region. This Analysis Hint will help to increasethe accuracy of an analysis process.

This class may also include a property entitled “string Factoid {get;set;},” which specifies a particular “factoid” that is to be used forthe location in the document 1703 to which the AnalysisHint isapplicable. As known to those of ordinary skill in the art, factoidsprovide hints to a recognition process as to an expected use of ink data(e.g., as regular text, digits, postal codes, filenames, and web URLs).This class may also include the properties entitled “RecognizerGuideGuide {get; set;}” and “OverrideLanguageId {get; set;}.” TheRecognizerGuide Guide {get; set;} property specifies the writing guidethat is to be applied to the location in the document 1703 to which theAnalysisHint is applicable. Writing guides may, for example, helpimprove the accuracy of a recognizer analysis process by specifying tothe user and informing the recognizer analysis process where the userwill write lines or characters. The OverrideLanguageId {get; set;}property specifies a Language Hint for the in the document 1703 to whichthe AnalysisHint is applicable. Setting a Language Hint causes theInkAnalyzer object to use the designated language instead of thelanguage specified on the context node.

This class may also include a property entitled “PrefixText {get;set;},” which specifies the text that is written or typed prior to aline of ink that is to be recognized. Still further, this class mayinclude a property entitled “RecognitionModes RecognitionFlags {get;set;},” which specifies particular type of modes a recognition processshould respect at the location in the document 1703 to which theAnalysisHint is applicable. Still further, this class may include aproperty entitled “SuffixText {get; set;},” which specifies the textthat is written or typed after to a line of ink that is to berecognized, and a property entitled “WordList WordList {get; set;},”which specifies a particular set of words that should be used by arecognition analysis process. Word lists may be used when the expectedrecognition results are known before the user has actually written inputdata, such as a list of medical terms that are expected to be writteninside a medical form.

Still further, this class may include a property entitled “WordMode{get; set}.” If this value is “true,” then the analysis process willbias itself to return a single word for the entire analysis region. Itmay also include a property entitled “Coerce {get; set},” which, if“true,” will force the analysis process to confine its result to anyfactoid or wordlist value set in the relevant hint. This class may alsoinclude a property entitled “AllowPartialDictionaryTerms {get; set}.” Ifthis property value is “true,” then the recognition analysis processwill be allowed to return partial words from its recognition dictionary.

According to various examples of the invention, the Ink Analysis API mayfurther include an Analysis Region class. This class may include, forexample, multiple constructors for constructing an AnalysisRegionobject. For example, it may contain a first constructor for constructingan AnalysisRegion object having any region, a second constructor forconstructing an AnalysisRegion object based upon the parameters for atwo-dimensional rectangle, and a third constructor for constructing anAnalysisRegion object based upon four spatial coordinates. The defaultconstructor may, for example, create an empty region. This class mayalso include a number of properties. For example, this class may includea property entitled “Rectangle Bounds {get;},” which retrieves thebounding rectangle for the AnalysisRegion, a property entitled “IsEmpty{get;},” which indicates whether the relevant AnalysisRegion object hasan empty interior, and a property entitled “IsInfinite {get;},” whichindicates whether the relevant AnalysisRegion is set to infinite or not.

This class may also include a number of methods, such as a methodentitled “AnalysisRegion Clone( ),” which clones the relevantAnalysisRegion object. This class may also include a method entitled“Equals(AnalysisRegion otherRegion),” which tests whether the specifiedAnalysisRegion object (referred to as the otherRegion) is identical tothe relevant AnalysisRegion object. This method returns a value of“true” if the interior of the specified Analysis Region object isidentical to the interior of the relevant Analysis Region object, andotherwise returns a value of “false.”

This class may further include a method “Intersect(AnalysisRegionregionToIntersect),” which crops down the relevant AnalysisRegion objectto the specified analysis region. Thus, the resulting AnalysisRegionobject will only include areas that overlapped or intersected thespecified analysis region. This class may also include the methodentitled “Intersect(Rectangle rectangle),” which crops down the relevantAnalysisRegion object to the specified rectangle. Again, the resultingAnalysisRegion object will only include areas that overlapped orintersected the specified rectangle. It may also include the methodentitled “MakeEmpty( ),” which initializes the relevant AnalysisRegionobject to an empty interior, and the method entitled “MakeInfiniteo,”which sets the area occupied by the relevant AnalysisRegion to beinfinite. It may further include various methods for uniting orseparating differently defined areas, such as method entitled“Union(AnalysisRegion regionToUnion),” which specifies an AnalysisRegionobject to union or add to the relevant AnalysisRegion object, and themethod entitled “Union(Rectangle rectangle),” which unions a specifiedrectangle to the relevant Analysis Region object. With this method, therectangle may be specified in terms of the coordinate space for therelevant AnalysisRegion object. Of course, this class may includenumerous other methods for combining areas or extracting one area fromanother based upon any desired definition for the areas.

The Ink Analysis API may also have a Recognition Result class. As withmany of the previously discussed classes, the Recognition Result classmay include one or more constructors. For example, this class mayinclude a constructor entitled “RecognitionResult(Stream lattice)”,which constructs a RecognitionResults object from a given recognitionlattice. With various examples of the invention, a recognition latticeis a serialized form of the results from a recognition process. Thismethod may, for example, specify a recognition lattice as a byte arrayto be used for the construction of the relevant RecognitionResultobject. It may also include a constructor entitled“RecognitionResult(ContextNode node),” which constructs aRecognitionResults object from a given context node. It may also includea constructor entitled “RecognitionResult(string Text, intStrokeCount),” which constructs a RecognitionResults object from aspecified text value, which in turn is associated to a specified numberof strokes and might be used for correction if the recognition processdid not come up with an alternate recognition value corresponding to theactual handwritten ink data. Still further, this class may include aconstructor entitled “RecognitionResult(RecognitionResultleftRecognitionResult, RecognitionResult rightRecognitionResult),” whichconstructs a RecognitionResults object by merging two existingRecognition Results objects together.

The Recognition Result class may also include one or more properties,such as a property entitled “StrokeCollection StrokeCollection {get;},”which provides an array of stroke indexes representing a collection ofstrokes that are contained in a single ink object, and a propertyentitled “RecognitionAlternate TopAlternate {get;},” which provides thebest alternate of the recognition result. This class may also includethe property entitled “RecognitionConfidence RecognitionConfidence{get;},” which provides the level of confidence (e.g., strong,intermediate, or poor) of the top alternate selection for the currentresults from a recognition analysis process, and a property entitled“string TopString {get;},” which returns the best result string of theanalysis results from a recognition analysis process.

The Recognition Results class may also include a number of methods, suchas a method entitled “public RecognitionAlternateCollectionGetAlternateCollectionFromSelection (selectionStart, selectionLength,maximumAlternates),” which specifies a collection of alternates from aselection within the best result string of analysis results from arecognition analysis process, where each alternate corresponds to onlyone segment of ink. The input parameters for this method may include,for example, a value which specifies the start of the text selectionfrom which the collection of alternates is returned, a value thatspecifies the length of the text selection from which the collection ofalternates is returned, and a value that specifies the maximum number ofalternates to return. This method may then return theRecognitionAlternateCollection collection of alternates from a selectionwithin the best result string of the recognition result.

The Recognition Results class may further include a method entitled“RecognitionResult Merge(RecognitionResult left, string separator,RecognitionResult right).” This method may be used to create a newRecognitionResult object from a single string, resulting in a flatlattice, append a single string to the beginning or end of an existingRecognitionResult object, or concatenate a single string in between twoexisting RecognitionResult objects. This class may also include a methodentitled “ModifyTopAlternate(RecognitionAlternate alternate),” whichspecifies the recognition result to be modified with a known alternate.With some embodiments of the invention, by default the best resultstring of the results of a recognition analysis process corresponds tothe top alternate. However, this method can be used to specify thatalternates other than the top alternate are used in the results of therecognition analysis process. If the new top alternate results in adifferent segmentation than the previous one, the ModifyTopAlternatemethod will automatically update the context nodes to reflect thechanges. It should be noted that, in order to retrieve the alternatesthat can be used to modify the recognition result, this method call theGetAlternatesFromSelection method, discussed in detail below. This classmay also have a method entitled “Stream Save( ),” which persistentlymaintains the relevant RecognitionResults object in the form of arecognition lattice. A recognition lattice is a serialized format usedto express the results from a recognition process.

The Ink Analysis API may also have an Analysis Options enumerated type.This type may contain one or more fields that specify how ink data willbe analyzed by an analysis process, such a field entitled “constAnalysisOptions Default,” which enables all available options for theanalysis process. This field may, for example, enable text recognition,the use of tables, the use of lists, the use of annotations, the use ofconnectors and containers, and the use of intermediate results. Thistype may also include a field entitled “const AnalysisOptionsEnableAnnotations,” which enables and disables the detection ofannotations, a field entitled “const AnalysisOptionsEnableConnectorsAndContainers,” which enables and disables the detectionof connectors and containers, and a field entitled “constAnalysisOptions EnablelntermediateResults,” enables and disables thereturn of analysis results to the software application 1701 between theuse of different, sequential analysis processes (e.g., between a parsingprocess and a subsequent recognition process). This type may also have afield entitled “const AnalysisOptions EnableLists,” which enables anddisables the detection of lists, and a field entitled “constAnalysisOptions EnableTables,” which enables and disables the detectionof tables. This enumerated type may further include a field entitled“const AnalysisOptions EnableTextRecognition,” which enables anddisables a text recognition analysis process. It should be noted,however, that if additional analysis processes are available (ordifferent versions of the same analysis process), then this type mayinclude additional AnalysisOptions accordingly.

Still further, the Ink Analysis API may include anAnalysisResultsEventArgs class. This class may have a constructorentitled “public AnalysisResultsEventArgs( ),” which creates a datastructure that contains the analysis results and is returned to thesoftware application 1701 when the AnalysisResults event is raised. Thisclass may also include a property entitled “InkAnalyzer InkAnalyzer{get;},” which identifies the InkAnalyzer object that performed theanalysis process.

The API may also have a Line class, which may be useful with some typesof operating systems which recognize the use of a “Line” objectrepresenting a geometric line. This class may include a constructor,such as a constructor entitled “public Line(Point beginPoint, PointendPoint),” which creates a Line object. This class may also includevarious properties, such as a property entitled “public Point BeginPoint{get; set;},” which represents the beginning point of the line objectand a property entitled “public Point EndPoint {get; set;},” whichrepresents the ending point of the line object.

In addition to these classes, the Ink Analysis API may also contain aRecognition Alternate class. This class may include elementsrepresenting the possible word matches for segments of ink that arecompared to a recognizer's dictionary. For example, this class mayinclude a property entitled “Line Ascender {get;},” which provides theascender line of a RecognitionAlternate object that exists on a singleline (with a line being represented as two points), a property entitled“public Line Baseline {get;},” which provides the Baseline of aRecognitionAlternate object that exists on a single line, and a propertyentitled “Line Descender {get;},” which provides the descender line of aRecognitionAlternate object that exists on a single line. This class mayalso include a property entitled “RecognitionResult Extract {get;},”which provides a RecognitionResults object for the currentRecognitionAlternate object. This property can be used, for example, toextract the RecognitionResult object for a word from theRecognitionResult object for a line containing that word.

It may also include the property entitled “Line Midline {get;},” whichprovides the midline for a RecognitionAlternate object that exists on asingle line, a property entitled “StrokeCollection Strokes {get;},”which provides the collection of strokes that are contained in an inkobject (that is, it provides a StrokeCollection representing the strokesthat are associated to the RecognitionResult), and a property entitled“StrokeCollection[ ] StrokesArray {get;},” which provides a collectionof strokes that are contained in one or more ink objects, representingthe strokes that are associated with the RecognitionResult. This classalso may include a property entitled “RecognitionConfidenceRecognitionConfidence {get;},” which provides the level of confidence(e.g., strong, intermediate, or poor) that a recognition analysisprocess has determined in the recognition of a RecognitionAlternateobject or of a gesture. For non-line nodes, the lowestRecognitionConfidence of the children of the relevant context nodes willbe returned. It may also contain the property entitled “stringRecognizedString {get;}” which specifies the result string of thealternate. Thus, for any context node above a word context node, theresults string is concatenated together by this method. For example, aline node will contain a results string that in turn contains theresults of all its children or word nodes. A paragraph node will thencontain a results string that contains the results of all its childrenor line nodes.

The Recognition Alternate class may also contain one or more methodsincluding, for example, a method entitled “StrokcCollection[ ]GetStrokesArrayFromTextRange(int selectionstart, int selectionlength),”which specifies a StrokeCollection from each ink object that correspondsto the known text range. This class may also contain a method entitled“StrokeCollection[ ] GetStrokesFromStrokesArrayRanges(StrokeCollection[] strokesArray),” which specifies the smallest collection of strokesthat contains a known input collection of strokes and for which therecognizer can provide alternates. More particularly, the strokes arereturned by an array of ink objects each containing an array of strokeindexes for the collection It should be noted that the collection of inkstrokes returned by this method may match the input collection, or itmay be larger if the input collection matches only part of the smallestrecognition result that includes all of the input strokes. This classmay further include a method entitled “StrokeCollectionGetStrokesFromStrokesRanges(StrokeCollection strokes),” which specifiesthe smallest collection of strokes that contains a known inputcollection of strokes and for which the recognizer can providealternates, and a method entitled “StrokeCollectionGetStrokesFromTextRange(int selectionstart, int selectionlength),” whichspecifies the StrokeCollection that corresponds to the known text range.

This class may further include a method entitled “voidGetTextRangeFromStrokes(ref int selectionstart, ref int selectionend,StrokeCollection strokes),” which specifies the smallest range ofrecognized text for which the recognizer can return an alternate thatcontains a known set of strokes, and a method entitled “voidGetTextRangeFromStrokesArray(ref int selectionstart, ref intselectionend, StrokeCollection[ ] strokesarray),” which specifies thesmallest range of recognized text for which the recognizer can return analternate that contains a known set of strokes. It also may have amethod entitled “RecognitionAlternateCollectionSplitWithConstantPropertyValue(GUID propertyType),” which returns acollection of alternates, which are a division of the alternate on whichthis method is called. Each alternate in the collection containsadjacent recognition segments which have the same property value for theproperty passed into the method. For example, this method can be used toobtain alternates that divide an original alternate by level ofconfidence boundaries (strong, intermediate, or poor) in the recognitionresult, line boundaries, or segment boundaries. It may further include amethod entitled “byte[ ] GetPropertyValue(GUID propertyType),” whichspecifies the value of a known property of the alternate, such as therecognizer's confidence in the alternate. Not all recognition analysisprocesses will provide a value for all property types, however. Thus,this method provides the data for the types supported by the relevantrecognition analysis process.

The Ink Analysis API may also include a Recognition Alternate Collectionclass. Like many of the classes discussed above, this class may includea constructor, entitled “RecognitionAlternateCollection( ),” forcreating a RecognitionAlternateCollection object. This class may alsoinclude a number of properties, such as a property entitled “Count{get;},” which provides the number of objects or collections containedin a collection of alternate recognition values, a property entitled“IsSynchronized {get;},” which provides a value indicating whetheraccess to the collection of alternate recognition values is synchronizedwith the software application 1701 (i.e., “thread safe”), and a propertyentitled “SyncRoot {get;},” which provides the object that can be usedto synchronize access to the collection of alternate recognition values.

This class may also contain one or more methods, such as a methodentitled “virtual void CopyTo(Array array, int index),” which copies allof the elements of the current collection of alternate recognitionvalues to the specified one-dimensional array, starting at the specifieddestination array index, and a method entitled “IEnumeratorIEnumerable.GetEnumerator( ),” which is a standard implementation ofIEnumerable that enables callers to use the for each construct toenumerate through each RecognitionAlternate in the collection ofalternate recognition values. This class may also include a methodentitled “RecognitionAlternateCollectionEnumerator GetEnumeratoro,”which returns a RecognitionAlternateCollectionEnumerator that containsall of the objects within the collection of recognition alternatevalues. This method may be used, for example, to retrieve each object inthe collection of recognition alternate values.

The Ink Analysis API may additionally include a Recognition Confidenceenumeration and a Recognition Mode enumeration, each of which maycontain one or more fields relating to a recognition analysis process.For example, the Recognition Confidence class may contain multiplefields, such as a field entitled “Intermediate,” indicating that therecognition analysis process is confident that the correct result is inthe list of provided alternate recognition values, a field entitled“Poor,” which indicates that the recognition analysis is not confidentthat the result is in the list of provided alternate recognition values,and a field entitled “Strong,” which indicates that the recognitionanalysis process is confident that the best alternate in the alternaterecognition values is correct.

Likewise, the Recognition Mode class may include fields that thatspecify how a recognition analysis process interprets electronic inkdata and thus determines a recognition result string. For example, thisclass may include a field entitled “Coerce,” which specifies that therecognition analysis process coerce a recognition result based on afactoid that was specified for the context, and a field entitled “Line,”which specifies that the recognition analysis process treat theelectronic ink data as a single line. This class also may include afield entitled “None,” which specifies that the recognition analysisprocess apply no recognition modes, and a field entitled “Segment,”which specifies that the recognition analysis process treat theelectronic ink data as forming a single word or character. Still furtherthis class may include a field entitled “TopInkBreaksOnly,” whichdisables multiple segmentation.

Still further, the Ink Analysis API may include a Context Link class,which defines how two context nodes may be linked together. TheContextLink object by itself represents which two context nodes arelinked, the direction of the link, and the type of link. This class mayinclude a property entitled “ContextNode SourceNode{get;},” whichspecifies the source context node that is being linked from anothercontext node, a property entitled “ContextLinkType LinkType{get;},”which specifies the type of link relationship that exists between thesource and destination context nodes, and a property entitled“CustomLinkType{get;},” which specifies that a custom link is beingused. This situation would occur when an application decides to use thelinking system of the Ink Analyzer API to represent application specificlinks beyond what the API can recognize.

This class may also include a property entitled “ContextNodeDestinationNode {get;},” which specifies the destination context nodethat is being linked from another context node. There may be twoconstructors available to this class, which create a relationshipbetween existing source and destination context nodes.

This class may also include an enumeration entitled “ContextLinkTypeenum,” which defines the type of relationship shared by two contextnodes. These various link types may include, for example, an “AnchorsTo”type, which describes that one node is anchored to the other node. Bothnodes can use the SourceNode or DestinationNode property based on theparsing situation. The link types may also include the type “Contains,”which describes that the one node contains the other node. With thisrelationship, the container node could be referenced as the SourceNode,while the containee node could be referenced as the DestinationNode. Thelink types may further include a “PointsTo” type, which describes thatone node is pointing to another node. For this relationship, the nodedoing the pointing could be referenced as the SourceNode, while the nodebeing pointed to could be referenced as the DestinationNode. Stillfurther, the link types may have a “PointsFrom” type, which describesthat one node is pointing from the other node. In this relationship, thenode pointing away from the other node could be referenced as theSourceNode, while the node being pointed from could be referenced as theDestinationNode.

The link types may additionally include a “SpansHorizontally” type,which describes that one node runs the length horizontally of anothernode, and a “SpansVertically” type, which describes that one node runsthe length vertically of another node. For these types, the nodecovering (strike out, underline, margin bar) the other node, usuallywritten last, could be referenced as the SourceNode, while the nodebeing spanned could be referenced as the DestinationNode. The link typesmay also include a “Custom” type, which describes that a custom linktype has been used. When this value is used, the “CustomLinkType”property on the ContextLink object could provide more details as to thepurpose of this link.

Accordingly, the Ink Analyzer API provides a variety of functions andservices for asynchronously analyzing electronic ink in a document, andthen subsequently reconciling the results of the analysis process withthe current state of the document as described in detail above. Further,it should be appreciated that the various classes described above can beapplied to a variety of operating systems and environments, such as theMicrosoft Windows operating environment, the Microsoft COM operatingenvironment, a Unix or Linux operating environment, or any othersuitable computer operating environment. Moreover, it should beappreciated that an application programming interface according tovarious implementations of the invention may omit one or more of theclass components described above, or may include additional componentsto provide a desired service or functionality.

Reconciliation

As discussed in detail above, various examples of the invention allowthe software application 1701 to continue to operate while unanalyzedelectronic ink in the document 1703 is analyzed by a background analysisprocess. Because of this, the software application 1701 may modify thedocument 1703 in a number of ways that will conflict with the results ofanalysis process. For example, the software application 1701 may enternew electronic ink data 1705 into the document 1703, or delete existingelectronic ink data 1705 from the document 1703. Still further, thesoftware application 1701 may edit existing electronic ink data 1705,such as by moving the position of existing electronic ink data 1705 orchanging the properties of existing electronic ink data 1705. Stillfurther, the software application 1701 may add, delete, or modifynon-ink document elements 1707 in ways that impact existing electronicink data 1705. For example, the software application 1701 may deletetypewritten text that has been annotated with electronic ink data 1705.

The software application 1701 may additionally “pin” existing electronicink data 1705, so as to prohibit its modification by the analysisprocess. For example, if a user manually specifies a layout orclassification for a group of ink strokes, then the software application1701 may designate that those ink strokes remain in that specific layoutor with that classification regardless of the results produced by aparsing process. Similarly, a user may specify a particular recognitionresult for a group of ink strokes, regardless of the results produced bya recognition process.

Various types of pinning may be employed according to differentimplementations of the invention. For example, the ink analysis tool1901 may allow the software application 1701 to “hard” pin ink. Withthis arrangement, no ink strokes can be added to any of the leaf nodesbelow the pinned node, no strokes can be removed from any of the leafnodes below the pinned node, no adding or removing of child nodes arepermitted, and no re-parenting of any nodes below the pinned node arepermitted. Alternately or additionally, the ink analysis tool 1901 maypermit “hard” pinning with late strokes, which allows for late strokesto be added in under specified conditions, prohibits strokes from beingremoved from any of the leaf nodes below the pinned node, prohibits theaddition or removal of child nodes, and prohibits re-parenting of anynodes below the pinned node. Still further, the ink analysis tool 1901may allow the software application 1701 to alternately or additionally“soft” pin ink. With this arrangement, no strokes can be removed fromany of the leaf nodes below the pinned node, there are specified rulesto allow for adding of strokes (this allows for late strokes to be addedin), and regrouping, adding, and removing of child nodes are allowed. Itshould be noted that pinning can be removed, and, once pinning has beenremoved, the formerly pinned nodes and their children may then beconsidered “dirty” or in need of a reanalysis.

Still further, the ink process according to various examples of theinvention may employ multiple analysis processes, as discussed in detailabove. Accordingly, the results of an earlier analysis process maymodify electronic ink data 1705 while a second, subsequent analysisprocess is executing. Accordingly, the results of an analysis processmust be reconciled with the current state of the document 1703, so thatonly those results that are valid for the current state of the document1703 are applied to its analysis context object 1709. That is, thecurrent analysis context object 1709 (and, in some cases, the results ofthe analysis process) is modified so as to omit discrepancies or“collisions” between the results of the analysis process and the currentstate of the document 1703.

It should be noted that, in order for the results of the reconciliationprocess to be valid, the state of the document 1703 should not changeduring the reconciliation process. The reconciliation process may thusbe performed using the primary thread on which the software application1701 is run, and executing the reconciliation process may temporarilyhalt the operation of the software application 1701. Alternately, othertechniques, such as data structure locking, may be employed to ensurethat the state of the document 1703 does not change during thereconciliation process. Accordingly, it is desirable to perform thereconciliation process as quickly as possible, in order to prevent auser from becoming dissatisfied with the performance of the softwareapplication 1701. Another consideration for the reconciliation processis its effect on the performance of the analysis process run on theseparate background analysis thread. If discrepancies between thecurrent analysis context object 1709 (that is, the analysis contextobject 1709 reflecting the current state of the document 1703) and theanalysis results are too broadly defined, then large amounts ofelectronic ink will be reanalyzed unnecessarily. Of course, still otherways of protecting the integrity of the document during reconciliationmay be used without departing from the invention.

With various examples of the invention, the analysis process and thereconciliation process may adhere to one or more of the followingconventions in order improve the efficiency and convenience of thereconciliation process. First, the analysis process may reuse nodes fordocument element in the document independent analysis context object1903 as much as possible. That is, collisions should not be avoided bycreating new, unrelated nodes for document elements. In addition, thereconciliation process should respect “pinning” designated by thesoftware application 1701. While that analysis process will typicallycomply with pinning designations by software application 1701, thesoftware application 1701 may pin electronic ink data 1705 while theanalysis process is being executed. Further, the reconciliation processshould ensure that no empty nodes remain in the current analysis contextobject 1709 after the reconciliation process is completed. It should benoted, however, that one or more of these conventions may be omitted andnot followed according to alternate implementations of the invention.For example, some implementations of the invention may allow theanalysis object 1709 to contain empty nodes.

In addition to these conventions, the reconciliation process musttypically comply with interface rules dictated by the analysis contextobject 1709. For example, with some implementations of the invention,the analysis context object 1709 may not allow a node for a documentelement to be deleted unless it has no child nodes.

As previously noted, a collision occurs when the analysis process makesa change to the document independent analysis context object 1903 thatconflicts in some fashion with a change to the analysis context object1709 that was made after the analysis process was initiated. Collisionscan be divided into two types: mandatory collisions and discretionarycollisions.

Mandatory collisions occur when it is impossible to apply a change madeto the document independent analysis context object 1903 by the analysisprocess to the analysis context object 1709 for the current state of thedocument 1703. A mandatory collision will occur when, for example, thesoftware application 1701 has “pinned” or fixed a node in the analysiscontext object 1709 and the analysis process has changed thecorresponding node in the document independent analysis context object1903. A mandatory collision will also occur when the analysis processhas made any type of change to a node in the document independentanalysis context object 1903 but the software application 1701 hasdeleted the corresponding node from the analysis context object 1709,and when the software application 1701 has added strokes or child nodesto a node in the analysis context object 1709 when the analysis processhas deleted the corresponding node in the document independent analysiscontext object 1903. Further, a mandatory collision will occur when thesoftware application 1701 has deleted a node in the analysis contextobject 1709 when the analysis process has reordered or created a link tothe corresponding node in the document independent analysis contextobject 1903.

A discretionary collision occurs when the software application 1701 haschanged a value in the analysis context object 1709 that is related to avalue changed in the document independent analysis context object 1903by the analysis process, but the pinning constraints, the element reuseconstraints, and the inherent constraints of the interface for theanalysis context object 1709 could still allow the application of thechange made by the analysis process to the analysis context object 1709.A discretionary collision may still be applied as a change to theanalysis context object 1709 or avoided. Further, the reconciliationprocess may simply ignore some types of discretionary collisionsaltogether.

One graphic example of a discretionary collision occurs when an originalnode in both the analysis context object 1709 and the documentindependent analysis context object 1903 has child nodes A and B for inkstrokes A and B. The software application 1701 may then add a thirdchild C node for the ink stroke C in the analysis context object 1709,while the analysis process adds a third child node D for an ink stroke Dto the document independent analysis context object 1903. With variousembodiments of the invention, the reconciliation process may add thechild node D to the parent node in the analysis context object 1709based upon the analysis results. While this change to the parent node inthe analysis context object 1709 is not prohibited, however, it stillchanges the characteristics of the parent node in a manner that may beundesired by the software application 1701. For example, the inkassociated with the parent node may subsequently be considered analyzed,and may not be reanalyzed to take into account the effect of the ink Cto the group of ink strokes. Further, the recognition results for theparent node might now be referring to the wrong child nodes or strokes,and that might never again be corrected as well.

Accordingly, various examples of the invention will not apply changesfor a discretionary collision when updating the analysis context object1709 based upon the results of an analysis process. While this criteriamay require additional processing to identify and block changes basedupon discretionary collisions, this criteria is relatively easy toimplement and simple to maintain. Of course, still other examples of theinvention may implement changes corresponding to discretionarycollisions according to other criteria. More particularly, thesealternate examples may implement changes from discretionary collisionsthat do not create permanent logically inconsistent relationships in theanalysis context object 1709.

It should also be noted that collisions may have a transitive effect, inthat one collision may create another. For example, an analysis processmay create a node L for a line and then create a node W for a word as achild node of node L. If the creation of the node L was not applied tothe analysis context object 1709 due to a collision of any kind, thenthe creation of the node W will be a mandatory collision.

Various examples of the invention may employ a log-based approach toreconcile the results of an analysis process with the current state of adocument 1703. In this log-based approach, the document independentanalysis context object 1903 includes a log of changes to the documentindependent analysis context object 1903 made by the analysis process.The log may be in the form of, for example, a list of change records.Each change record may then include the type of change that was made (byidentifying, e.g., the method that was called to change the documentindependent analysis context object 1903), the document element uponwhich the change was made (by identifying, e.g., the node in thedocument independent analysis context object 1903 on which the methodwas called), and any information needed to recreate the arguments forthe method call. Advantageously, because the document independentanalysis context object 1903 is implemented by the ink analysis tool1901 and the analysis processes, the change log may be invisible to thesoftware application 1701 (although the log alternately may be exposedto the application 1701, if desired).

In order to execute the reconciliation process using the change logapproach, the ink analysis tool 1901 examines each change record in thechronological order of the changes. That is, the ink analysis tool 1901identifies each change made to the document independent analysis contextobject 1903. For each change, the ink analysis tool 1901 may implementthe process illustrated in FIG. 27. First, in step 2701, the inkanalysis tool 1901 attempts to access the corresponding nodes in thecurrent analysis context object 1709 that are needed to apply thechange. It should be noted that this retrieval step may fail if thesoftware application 1701 has deleted one of more of the necessary nodesfrom the analysis context object 1709, resulting in a mandatorycollision.

Next, in step 2703, the ink analysis tool 1901 determines if the changecreates a mandatory or discretionary collision. The procedure for makingthis determination will be explained in more detail below. In step 2705,the ink analysis tool 1901 either makes the change or prohibits thechange if it creates a mandatory collision or a discretionary collisionforbidden by the criteria for the reconciliation process. For example,if the change creates a mandatory collision or a discretionary collisionforbidden by the criteria for the reconciliation process, then the inkanalysis tool 1901 may block changes to the nodes in the analysiscontext object 1709 representing the corresponding region of thedocument 1703 in which the change was to be made. If, on the other handthe change is applied, then the ink analysis tool 1901 may call theappropriate method to make the desired change to the necessary nodes inthe analysis context object 1709.

If the analysis process adds a new element node to the analysis contextobject 1709 but then fails to move stroke nodes to the new node, thenthe analysis process also will not have tried to delete the element nodeon the assumption that stroke nodes were moved to the new nodessuccessfully. Thus, there will be an element node in the documentindependent analysis context object 1903 that corresponds to an emptynode in the current analysis context object 1709. Accordingly, once allof the changes to the analysis context object 1709 have been processed,in step 2707 the ink analysis tool 1901 reviews the document independentanalysis context object 1903 to delete any “empty” nodes in the analysiscontext object 1709 that correspond to nodes in the document independentanalysis context object 1903. This empty node deletion step is optionaland may be omitted without departing from the invention.

It should be noted that the document independent analysis context object1903 should not contain any empty nodes, and the reconciliation processshould prohibit empty nodes from being created in the documentindependent analysis context object 1903. It should also be noted thatthis step will not attempt to delete the root node of the analysiscontext object 1709, even if it is empty, as an exception. Lastly, instep 2709, the ink analysis tool 1901 will identify any collisionsbetween the analysis results in the document independent analysiscontext object 1903 and the current analysis context object 1709 to thesoftware application 1701, so that the software application 1701 caninclude the regions of the document 1703 affected by the collisions in asubsequent analysis process.

Returning now to the detection of collisions in step 2703 above, onceall of the nodes in the analysis context object 1709 corresponding tochanges in the document independent analysis context object 1903 areaccessed, all other possible mandatory collisions for each node in theanalysis context object 1709 can be detected statically (or,alternately, the absence of a mandatory collision may be detected foreach node). More particularly, mandatory collisions can be detectedbased upon the rules designated by the interface for the analysiscontext object 1709.

Discretionary collisions, however, typically cannot be identifiedwithout additional state information regarding the document 1703, asthese changes are not mandated by the interface of the analysis contextobject 1709 but instead are based upon discretionary choices aboutfavoring changes made by the software application 1701 over the changesmade by the analysis process when both have impacted the same node inthe analysis context object 1709. These collisions can instead bedetected by comparing the current analysis context object 1709 with theoriginal version of the document independent analysis context object1903, to determine which nodes in the analysis context object 1709 havebeen changed by the software application 1701.

For example, the reconciliation criteria may define that the addition ordeletion of a child stroke node from a parent node by the softwareapplication 1701 is a discretionary collision for that parent node. Todetermine whether such a change has occurred, the ink analysis tool 1901can review the child stroke nodes depending from the node in the currentanalysis context object 1709, and compare their number and Guids (orother unique identifier) to the child stroke nodes depending from thecorresponding node in the original version of the document independentanalysis context object 1903. If the child stroke nodes match in theseaspects (and any other desired aspects), then the ink analysis tool 1901can apply the changes made by the analysis process to the parent node inthe analysis context object 1709.

Continuing this example, the next change in the log entry may consist ofanother stroke node being moved to depend from the parent node in thedocument independent analysis context object 1903. If there are nomandatory collisions from this change, then the ink analysis tool 1901is allowed to make the corresponding change to the analysis contextobject 1709. When the ink analysis tool 1901 checks the original versionof the document independent analysis context object 1903 to determine ifa discretionary collision exists, however, it will conclude that theparent node in the current analysis context object 1709 has one moredependent stroke node than the parent node in the original version ofthe document independent analysis context object 1903, so it willerroneously determine that a discretionary collision exists (that is, itwill determine that a collision exists based upon changes that it hasmade).

Accordingly, the log-based reconciliation process should exclude priorchanges made by the reconciliation from the comparison between theanalysis context object 1709 current and the original version of thedocument independent analysis context object 1903. With various examplesof the invention, this exclusion can be made by comparing all nodes inthe current analysis context object 1709 with their corresponding nodesin the original version of the document independent analysis contextobject 1903, before examining any change list entries, and keeping alist of the nodes that collided.

Alternately or additionally, various examples of the invention maymaintain a cache of the elements in the current analysis context object1709 corresponding to elements in the document independent analysiscontext object with the analysis results that is used whenever thecorresponding elements are retrieved. There is no preliminary pass, butthe cache is populated the first time a corresponding element has beendetermined to be free of discretionary collisions. Optionally, the cachecan also keep track of which elements in results had discretionarycollisions. This approach has better performance than thediscretionary-collision-finding-pass approach when the change log isshort, but may have worse performance if the document independentanalysis context object 1903 with the analysis results contains manynodes. It is also no more complex than the other approach.

It should be noted that the parent context nodes of elements in thecache should also be cached. More particularly, a change to a childcontext node will be considered a change to the properties of its parentcontext node. Thus, the parent context node of a context node stored inthe cache also needs to be evaluated for changes made by the softwareapplication 1701 at this point. The caching of parent nodes for eachcontext node in the cache needs to be repeated up the tree (e.g., fromparent node to grandparent node to great-grandparent node) until theroot node is passed or until changes are detected. In many situations,however, this repetition is only a few nodes as a tree typically willnot become very deep.

It also should be noted that, with various examples of the invention,the original version of the document independent analysis context object1903 is only used for detecting discretionary collisions. If thedetection of discretionary collisions is unnecessary with an example ofthe invention, then both the original version of the documentindependent analysis context object 1903 and the corresponding elementscache could be eliminated. This “log-based” approach may be easier tomaintain than the “comparison-based” approach described below, as itrequires less searching to determine what changes were made by theanalysis process, and operations on the document independent analysiscontext object 1903 (such as “delete node,” or “create node”) arehandled separately, so adding a new type of operation does not tend toaffect the other operations.

Instead of the “log-based” technique for reconciling the analysisresults with the current state of the document 1703, various examples ofthe invention may employ a “comparison-based” approach forreconciliation. The main distinguishing feature of the comparison-basedapproach is that no log is kept of the changes made to the documentindependent analysis context object 1903, so this technique does notcollect information about what the analysis process did other than bycomparing the document independent analysis context object 1903containing the analysis results with the original version of thedocument independent analysis context object 1903. Therefore, with thisapproach, the original version of the document independent analysiscontext object 1903 is always required, irrespective of any judgmentsabout discretionary collisions.

Using this approach, the ink analysis tool 1901 first builds a strokemap. That is, for every ink leaf node in the original version of thedocument independent analysis context object 1903, if there is acorresponding node in the current analysis context object 1709, then theleaf node is added to a hash table (or other suitable data structure).Thus, the hash table maps stroke GUIDs (or other unique nodeidentifiers) in the original version of the document independentanalysis context object 1903 to leaf node references in the currentanalysis context object 1709.

Next, the ink analysis tool 1901 identifies all nodes that the softwareapplication 1701 has changed in the analysis context object 1709. Thismay be done using the techniques for determining discretionarycollisions described in detail above. For each node in the originalversion of the document independent analysis context object 1903, ifthere is a corresponding node in the current analysis context object1709 and it differs from the node in the original version of thedocument independent analysis context object 1903 in some significantway, then the ink analysis tool 1901 determines that this node has beenchanged by the application and is a potential collision. References tosuch nodes are saved in a first list corresponding to analysis resultsnodes that should not be added to the analysis context object 1709(hereafter referred to as the resultsNodesNotToAdd list) and a secondlist of nodes that create discretionary collisions.

For each node in the original version of the document independentanalysis context object 1903, the ink analysis tool 1901 looks up thecorresponding nodes in both the document independent analysis contextobject 1903 with the analysis results and the current analysis contextobject 1709. For each node in the analysis context object 1709, the inkanalysis tool 1901 determines if the software application 1701 deletedthe node. Such nodes exist in the original version of the documentindependent analysis context object 1903, but have no corresponding nodein the analysis context object 1709. The corresponding node in thedocument independent analysis context object 1903 with the analysisresults is added to the resultsNodesNotToAdd list if it exists.

Next, the ink analysis tool 1901 determines if the analysis processdeleted the node from the document independent analysis context object1903. This is detected when there is a corresponding node in theanalysis context object 1709 current and it has not changed, but thereis not a corresponding node in the document independent analysis contextobject 1903 with the analysis results. Nodes deleted by the analysisprocess may be saved in a list of deleted nodes. Such a node is notadded to the analysis context object 1709 current, but it does not go inthe resultsNodesNotToAdd list because there is no corresponding node inthe document independent analysis context object 1903 with the analysisresults.

If the software application 1701 has neither deleted nor changed thenode, and the analysis process did not delete the node, then the inkanalysis tool 1901 may determine if the analysis process has changed thenode. The same techniques that were described above for use in detectingchanges made by the software application 1701 can be used to detectchanges made by the analysis process. Nodes that have been changed bythe analysis process are added to the resultsNodesNotToAdd list, and thechanges are propagated by calling appropriate methods on the nodes inthe analysis context object 1709. If neither the software application1701 nor the analysis process changed or deleted a node, then nothinghas happened to that node, and the ink analysis tool 1901 add the nodeto the resultsNodesNotToAdd list, as the node exists in the documentindependent analysis context object 1903 with the analysis results andis not to be added to the analysis context object 1709.

Next, for each node in the document independent analysis context object1903 with the analysis results, if the node is not in theresultsNodesNotToAdd list, then the ink analysis tool 1901 may propagateany changes to the node by the analysis process by creating acorresponding node in the analysis context object 1709. The traversal ofthe nodes in the analysis results may be performed using a top-down,pre-order traversal, so that parent nodes are guaranteed to be createdbefore child nodes.

When creating a new leaf node in the analysis context object 1709,whatever ink strokes associated with the node that are contained in theanalysis results may also be moved to the new node from other nodes inthe analysis context object 1709. The stroke map discussed above maythen be used to identify the source elements for moving the strokes. Inkstrokes are not moved if the source element does not exist (creating amandatory collision) or if the source element is contained in thediscretionary collision list also noted above. To save unnecessary callsto the analysis context object 1709, this ink analysis tool 1901 mayavoid calling the method to create a child context node if there is notat least one non-colliding stroke source node. The same stroke sourcechecking is also performed on non-ink leaf nodes, so that a node for aline is not created unless at least one of the line's constituent wordsis going to contain at least one successfully moved stroke, forinstance.

Other information then is also applied to the newly created node, suchas a recognition lattice. The recognition lattice is still applied evenif certain strokes could not be moved, creating an applied (that is,non-blocked) discretionary collision that results in a temporary logicalinconsistency. However, since the failed stroke moves are reflected inthe designation of the portion of the analysis context object 1709corresponding to a region of the document for which changes are blocked,the inconsistency is temporary, as the software application 1701 isadvised to re-analyze the blocked region.

For each node to be deleted from the analysis context object 1709, theink analysis tool 1901 list checks to see if the node can actually bedeleted now that all other edits and additions to the analysis contextobject 1709 have been performed. Nodes that are to be deleted and thatare actually empty of all child nodes and strokes are deleted from theanalysis context object 1709. Once such a node is deleted, all ancestornodes (up to but not including the root node) are deleted in successionuntil an ancestor with other remaining children is encountered.

Finally, the ink analysis tool 1901 makes a global comparison of nodeordering between the document independent analysis context object 1903with the analysis results and the analysis context object 1709, so as todetect and propagate the changes to the analysis context object 1709 bythe analysis process. It should be noted, however, that this comparisonignores the original version of the document independent analysiscontext object 1903, so it has no way of detecting changes to theordering made by the software application 1701. Next, for each containernode in the analysis results that has a corresponding node in theanalysis context object 1709, the ordering of the container nodes'children is compared. If both container nodes have exactly the same setof children, then the ordering in the analysis results is propagated tothe analysis context object 1709 by looping over the container's childlist in the analysis results until a node is found at the same positionin the container's list in the analysis context object 1709 that doesnot have the same GUID (or other type of identifier) as the child nodein the analysis results. When such a mismatch is found, thecorresponding node must be found further down in the child list in theanalysis context object 1709. The ink analysis tool 1901 then searchesthe rest of the child list in the analysis context object 1709 for thenode, and calls method to move the child node to correct the order forthat node in the analysis context object 1709. The ink analysis tool1901 then continues looping over nodes in the analysis results.

Of course, the assumption of identical lists does not hold true, sinceeither the analysis list or the software application 1701 could havedeleted or inserted nodes in either list. A “child list mapper” objectis used to simulate the assumption holding true, by presenting “pruned”lists that only contain elements that are held in common. The proceduredescribed above is then run on the mapped child lists, and the moves aretranslated to the real indexes and calls by the list mapper object.

Thus, the reconciliation techniques according to various examples of theinvention described above allow the results of an analysis process to beapplied to the current document elements in a document, even if thecontents of the document have changed since the analysis process wasinitiated. These reconciliation techniques therefore allow electronicink in a document to be analyzed asynchronously from the operation ofthe software application hosting the document. Further, thesereconciliation techniques may advantageously be employed by a variety ofdifferent software applications, including existing multithreadedsoftware applications with existing, proprietary locking or othersynchronization strategies.

Event Driven System

As discussed above, various examples of the invention create a“snapshot” of the state of a document by copying a document independentanalysis context object, and then asynchronously analyze the documentindependent analysis context object while the software applicationhosting the document continues to operation. Alternately, variousexamples of the invention may forego the use of the document independentanalysis context object for asynchronous ink analysis. Instead, theseexamples of the invention may use a sealed component to store all inkand semantic data for a document. More particularly, these examples ofthe invention recognizes two types of modifications that can be made toa document: ink events, such as adding, deleting, or modifying strokes;and structure events, such as grouping strokes into words, addingsemantic nodes, or associating text recognition results to strokes.Every event contains all data necessary to completely describe the eventto an external listener. For example an “add stroke” event will includeall of the stroke data. With these “rich” events, a listener canmaintain an exact duplicate of an ink object by applying events in theorder they were received.

FIG. 28 illustrates one example of how this arrangement may be employed,according to various examples of the invention. As seen in this figure,an application 2801 employs an ink analysis tool 2803. The ink analysistool 2803 maintains ink data 2805 and a document structure 2807 (e.g.,such as a tree structure) for the application 2801. The application alsoemploys an event queue 2809, a parser process 2811 and a recognitionprocess 2817. The parser process 2811 maintains a clone 2813 of the inkdata 2805 and a clone 2815 of the document structure 2807. Similarly,the recognition process 2817 maintains a clone 2819 of the ink data 2805and a clone 2821 of the document structure 2807.

When the application generates ink data, it provides the ink data to theink analysis tool 2803 via a method 2823. In response, the ink analysistool 2803 generates an event corresponding to a change in the ink data,adds a tag to every event, and defines the desired analysis process orprocesses as components that listen to the events with specified tags.For example, all user changes to ink may be marked with the tag“UserChange,” and an event 2825 with this tag is sent to the event queue2809 synchronously in response to the change. At some point in thefuture, the parser process 2811 and the recognition process 2817 willretrieve the tagged event from the event queue 2809.

A first analysis process (e.g., the parsing process 2811) would thenlisten to all events issued by the ink analysis tool 2803, and respondto those with the tag UserChange. The first analysis process would thenapply the changes specified by the event to its internal copy of the inkdata 2813 and the document structure 2815, analyze the data described inthe event, and then create and tag events 2827 generated by its changeswith the tag “ParserIChange.” These events 2827 would be relayed by theink analysis tool 2803 back to the event queue 2809. A second analysisprocess (e.g., the handwriting recognition process 2817) would thenlisten to events tagged with ParserI Change tag. In response, it wouldapply the changes specified by the event to its internal copy of the inkdata 2819 and the document structure 2821, and analyze the datadescribed in the events in response. The second analyzer would thencreate and tag an event 2829 with its analysis results with the tag“HandwritingRecognitionChange.” As the ink analysis tool 2803 receivesevents from the parser process 2811 and the recognition process 2817, itsends events 2831 to the application 2801 to indicate a change in thedocument structure 2807.

These embodiments of the invention could also support each analysisprocess by listening to events with more than one event, and to tag theevents from its changes with different tags based on internalprocessing. Accordingly, these alternate implementations of theinvention may also allow for analysis of electronic ink in a documentthat is asynchronous from the operation of the software applicationhosting the document.

CONCLUSION

While the invention has been described with respect to specific examplesincluding presently preferred modes of carrying out the invention, thoseskilled in the art will appreciate that there are numerous variationsand permutations of the above described systems and techniques that fallwithin the spirit and scope of the invention as set forth in theappended claims.

1. A computer-implemented method for asynchronous receipt and processingof electronic ink annotation of a document, comprising: generating afirst analysis context object, the first analysis context objectproviding a translation layer for a document model of a current state ofa relationship of elements in the document and comprising a tree datastructure for storing document elements in a hierarchical relationship;staffing a first thread, wherein the first thread updates the firstanalysis context object based upon a user interaction with the document,the user interaction including electronic ink annotation; upon an eventrequiring analysis of new data in the document: suspending execution ofthe first thread so as to prevent changes to the first analysis contextobject; starting a second thread, wherein the second thread generates asecond analysis context object corresponding to a portion of the firstanalysis context object, wherein the portion corresponds to a designatedregion of the document; upon completion of generation of the secondanalysis context object: suspending execution of the second thread;restarting the first thread; performing a first analysis of the secondanalysis context object to generate a third analysis context object fromthe second analysis context object, wherein the third analysis contextobject is generated by parsing the new data and modifying the secondanalysis context object based on the new data and further includesclassification information for the new data; upon completion of thefirst analysis: suspending execution of the first thread so as toprevent any changes to the first analysis context object; starting athird thread, wherein the third thread reconciles the third analysiscontext object with the first analysis context object to generate firstreconciled analysis results; upon completion of the reconciliation ofthe first analysis context object and the third analysis context object:updating the first analysis context object with the first reconciledanalysis results; suspending execution of the third threat; andrestarting the first thread.
 2. The method according to claim 1, whereinthe first analysis context object includes a member selected from thegroup of: a paragraph node, a line node, a word node, and a drawingnode.
 3. The method according to claim 1, wherein the first analysiscontext object includes a member selected from the group of: a groupnode, a paragraph node, a line node, an ink word node, an electronicdrawing node, an ink drawing node, a list node, a list item node, anelectronic bullet node, an ink bullet node, an electronic text wordnode, an image node, a table node, a row node, and a cell node.
 4. Themethod according to claim 3, wherein the second analysis context objectis selected from the group of: an unclassified ink node, a group node, aparagraph node, a line node, an ink word node, an ink drawing node, alist node, a list item node, an ink bullet node, a table node, a rownode, and a cell node.
 5. The method according to claim 1, wherein theportion includes at least one of electronic text, an image, a table, alist, a graph, a spreadsheet, a chart, or a drawing.
 6. The methodaccording to claim 1, wherein the new data is an electronic inkannotation, the annotation includes at least one unclassified ink node.7. The method according to claim 6, further comprising: rendering theportion and the electronic ink annotation, wherein the electronic inkannotation is located at a first position with respect to the portion;changing data associated with the portion such that a locationassociated with the first context node changes to a second position; andrendering the electronic ink annotation and the portion with the changeddata, wherein the electronic ink annotation is rendered at a thirdposition with respect to the first portion at least in part based on thesecond position of the first context node.
 8. The method according toclaim 6, wherein data associated with the first context node and thesecond context node enable the electronic document to be rendered suchthat the electronic ink annotation contains the portion of the document.9. The method according to claim 6, wherein data associated with thefirst context node and the second context node enable the electronicdocument to be rendered such that the electronic ink annotationunderlines the portion of the document.
 10. The method according toclaim 6, wherein data associated with the first context node and thesecond context node enable the electronic document to be rendered suchthat the electronic ink annotation strikes out the portion of thedocument.
 11. The method according to claim 6, wherein data associatedwith the first context node and the second context node enable theelectronic document to be rendered such that a first region of theelectronic ink annotation points between a second region of theelectronic ink annotation and the portion of the base document.
 12. Thesystem according to claim 6, wherein the portion corresponds to one ormore words of typewritten text in the electronic document, and whereinthe annotation is an electronic ink annotation of the one or more wordsof typewritten text.
 13. The system according to claim 6, wherein theportion corresponds to an electronic ink drawing in the electronicdocument, and wherein the annotation is an electronic ink annotation ofthe electronic ink drawing.
 14. The method according to claim 1, whereinthe first context node and the second context node share at least onecommon parent node.
 15. A computer-readable storage medium includingcomputer-executable instructions, the instructions when executedperforming the method of claim
 1. 16. The method according to claim 1,further comprising: after suspending execution of the first threadstarting a caching thread for receiving changes to the document basedupon future user interaction; after suspending execution of the secondthread, suspending execution of the caching thread; upon completion ofthe first analysis and after suspending execution of the first thread,restarting the caching thread; and after suspending execution of thethird thread, suspending the execution of the caching thread.
 17. Thesystem for asynchronous receipt and processing of electronic inkannotation of a document, comprising: an input for receiving electronicink input data in the document, wherein The document is an electronicdocument; and a processor programmed and adapted to: generate a firstanalysis context object, the first analysis context object providing atranslation layer for a document model of a current state of arelationship of elements in the document and comprising a tree datastructure for storing document elements in a hierarchical relationship;start a first thread, wherein the first thread updates the firstanalysis context object based upon a user interaction with the document,the user interaction including electronic ink annotation; upon an eventrequiring analysis of new data in the document: suspend the execution ofthe first thread so as to prevent changes to the first analysis contextobject; start a second thread, wherein the second thread generates asecond analysis context object corresponding to a portion of the firstanalysis context object, wherein the portion corresponds to a designatedregion of the document; upon completion of generation of the secondanalysis context object: suspend the execution of the second threat;restart the first threat; perform a first analysis of the secondanalysis context object to generate a third analysis context object fromthe second analysis context object, wherein the third analysis contextobject is generated by parsing the new data and modifying the secondanalysis context object based on the new data; upon completion of thefirst analysis: suspend execution of the first thread so as to preventany changes to the first analysis context object; start a third thread,wherein the third thread reconciles the third analysis context objectwith the first analysis context object to generate first reconciledanalysis results; upon completion of the reconciliation of the firstanalysis context object and the third analysis context object: updatethe first analysis context object with the first reconciled analysisresults; and suspend the execution of the third thread; and restart thefirst thread.
 18. The system according to claim 17, wherein the firstanalysis context object includes a member selected from the group of: aparagraph node, a line node, a word node, and a drawing node.
 19. Thesystem according to claim 17, wherein the first analysis context objectincludes a member selected from the group of: a group node, a paragraphnode, a line node, an ink word node, an electronic drawing node, an inkdrawing node, a list node, a list item node, an electronic bullet node,an ink bullet node, an electronic text word node, an image node, a tablenode, a row node, and a cell node.
 20. The system according to claim 19,wherein the second analysis context object is selected from the groupof: an unclassified ink node, a group node, a paragraph node, a linenode, an ink word node, an ink drawing node, a list node, a list itemnode, an ink bullet node, a table node, a row node, and a cell node. 21.The system according to claim 17, wherein the portion includes at leastone of electronic text, an image, a table, a list, a graph, aspreadsheet, a chart, or a drawing.
 22. The system according to claim17, wherein the new data includes an electronic ink annotation and priorto parsing the electronic ink annotation, the annotation includes atleast one unclassified ink node.
 23. The system according to claim 22wherein the processor is further programmed and adapted to: render theportion and the electronic ink annotation, wherein the annotation islocated at a first position with respect to the first portion, receiveinput indicating a change in data associated with the portion such thata location associated with the first analysis context object changes toa second position, and render the electronic ink annotation and theportion with the changed data, wherein the annotation is rendered at athird position with respect to the portion at least in part based on thesecond position of the first analysis context object.
 24. The systemaccording to claim 22, wherein data associated with the first analysiscontext object and the second analysis context object enable theelectronic document to be rendered such that the electronic inkannotation contains the portion of the document.
 25. The systemaccording to claim 22, wherein data associated with the first analysiscontext object and the second analysis context object enable theelectronic document to be rendered such that the electronic inkannotation underlines the portion of the document.
 26. The systemaccording to claim 22, wherein data associated with the first analysiscontext object and the second analysis context object enable theelectronic document to be rendered such that the electronic inkannotation strikes out the portion of the document.
 27. The systemaccording to claim 22, wherein data associated with the first analysiscontext object and the second analysis context object enable theelectronic document to be rendered such that a first region of theelectronic ink annotation points between a second region of theelectronic ink annotation and the portion of the document.
 28. Thesystem according to claim 22, wherein the portion corresponds to one ormore words of typewritten text in the electronic document, and whereinthe annotation is an electronic ink annotation of the one or more wordsof typewritten text.
 29. The system according to claim 22, wherein theportion corresponds to an electronic ink drawing in the electronicdocument, and wherein the annotation is an electronic ink annotation ofthe electronic ink drawing.
 30. The system according to claim 17,wherein the first analysis context object and the second analysiscontext object share at least one common parent node.